Tag: Top stories (418)

• Top Stories, Sep 14-20: Automating Every Aspect of Your Python Project; Deep Learning’s Most Important Ideas - Sep 21, 2020.
  
  Also: Statistics with Julia: The Free eBook; Online Certificates/Courses in AI, Data Science, Machine Learning from Top Universities; Autograd: The Best Machine Learning Library You're Not Using?; Implementing a Deep Learning Library from Scratch in Python

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• Top Stories, Sep 7-13: Free From MIT: Intro to Computer Science and Programming in Python - Sep 14, 2020.
  
  Also: Modern Data Science Skills: 8 Categories, Core Skills, and Hot Skills; AI Papers to Read in 2020; A Deep Learning Dream: Accuracy and Interpretability in a Single Model; Creating Powerful Animated Visualizations in Tableau; 8 AI/Machine Learning Projects To Make Your Portfolio Stand Out

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• Top August Stories: Know What Employers are Expecting for a Data Scientist Role in 2020; If I had to start learning Data Science again, how would I do it? - Sep 11, 2020.
  
  Also: Netflix's Polynote is a New Open Source Framework to Build Better Data Science Notebooks; Must-read NLP and Deep Learning articles for Data Scientists.

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• Top Stories, Aug 31 – Sep 6: Top Online Masters in Analytics, Business Analytics, Data Science – Updated - Sep 7, 2020.
  
  Also: How to Evaluate the Performance of Your Machine Learning Model; Which methods should be used for solving linear regression?; A Curious Theory About the Consciousness Debate in AI; If I had to start learning Data Science again, how would I do it?; PyCaret 2.1 is here: Whats new?

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• Top Stories, Aug 24-30: If I had to start learning Data Science again, how would I do it?; 4 ways to improve your TensorFlow model – key regularization techniques you need to know - Aug 31, 2020.
  
  Also: The NLP Model Forge: Generate Model Code On Demand; DeepMinds Three Pillars for Building Robust Machine Learning Systems; Beyond the Turing Test; Must-read NLP and Deep Learning articles for Data Scientists; How to Optimize Your CV for a Data Scientist Career

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• Top Stories, Aug 17-23: If I had to start learning Data Science again, how would I do it? - Aug 24, 2020.
  
  Also: Must-read NLP and Deep Learning articles for Data Scientists; Top Google AI, Machine Learning Tools for Everyone; Introduction to Federated Learning; Must-read NLP and Deep Learning articles for Data Scientists; These Data Science Skills will be your Superpower

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• Top Stories, Aug 10-16: Know What Employers are Expecting for a Data Scientist Role in 2020; The List of Top 10 Lists in Data Science - Aug 17, 2020.
  
  Also: 5 Different Ways to Load Data in Python; Facebook Uses Bayesian Optimization to Conduct Better Experiments in Machine Learning Models; Exploring GPT-3: A New Breakthrough in Language Generation; Unit Test Your Data Pipeline, You Will Thank Yourself Later; Going Beyond Superficial: Data Science MOOCs with Substance

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• Top July Stories: Data Science MOOCs are too Superficial - Aug 11, 2020.
  
  Also: A Layman's Guide to Data Science. Part 3: Data Science Workflow; The Bitter Lesson of Machine Learning; Free MIT Courses on Calculus: The Key to Understanding Deep Learning.

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• Top Stories, Aug 3-9: Know What Employers are Expecting for a Data Scientist Role in 2020 - Aug 10, 2020.
  
  Netflix's Polynote is a New Open Source Framework to Build Better Data Science Notebooks; Metrics to Use to Evaluate Deep Learning Object Detectors; Setting Up Your Data Science & Machine Learning Capability in Python; Which Data Science Skills are core and which are hot/emerging ones?

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• Top Stories, Jul 27 – Aug 2: Computational Linear Algebra for Coders; Awesome Machine Learning and AI Courses - Aug 3, 2020.
  
  Also: Essential Resources to Learn Bayesian Statistics; Deep Learning for Signal Processing: What You Need to Know; A Tour of End-to-End Machine Learning Platforms; I have a joke about …; First Steps of a Data Science Project

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• Top Stories, Jul 20-26: Data Science MOOCs are too Superficial - Jul 27, 2020.
  
  Also: Easy Guide To Data Preprocessing In Python; Data Mining and Machine Learning: Fundamental Concepts and Algorithms: The Free eBook; Recurrent Neural Networks (RNN): Deep Learning for Sequential Data; How Much Math do you need in Data Science?

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• Top Stories, Jul 13-19: The Bitter Lesson of Machine Learning - Jul 20, 2020.
  
  Also: 3 Advanced Python Features You Should Know; Understanding How Neural Networks Think; Free MIT Courses on Calculus: The Key to Understanding Deep Learning; How Much Math do you need in Data Science?

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• Top Stories, Jul 6-12: A Layman’s Guide to Data Science Workflow; Free MIT Courses on Calculus: The Key to Understanding Deep Learning - Jul 13, 2020.
  
  Top Stories post excerpt: Also: A Complete Guide To Survival Analysis In Python, part 1; PyTorch for Deep Learning: The Free eBook; Exploratory Data Analysis on Steroids

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• Top June Stories: How Much Math do you need in Data Science? Easy Speech-to-Text with Python - Jul 10, 2020.
  
  Also: Deep Neural Networks and the Jennifer Aniston Neuron; Don't Democratize Data Science.

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• Top Stories, Jun 29 – Jul 5: Speed up your Numpy and Pandas with NumExpr Package; Deploy Machine Learning Pipeline on AWS Fargate - Jul 6, 2020.
  
  Also: Getting Started with TensorFlow 2; An Introduction to Statistical Learning: The Free eBook; How Much Math do you need in Data Science?; Data Cleaning: The secret ingredient to the success of any Data Science Project

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• Top Stories, Jun 22-28: How Much Math do you need in Data Science? - Jun 29, 2020.
  
  Also: 4 Free Math Courses to do and Level up your Data Science Skills; Exploring the Real World of Data Science; Learning by Forgetting: Deep Neural Networks and the Jennifer Aniston Neuron; A TensorFlow Modeling Pipeline Using TensorFlow Datasets and TensorBoard

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• Top Stories, Jun 15-21: Easy Speech-to-Text with Python; A Complete guide to Google Colab for Deep Learning - Jun 22, 2020.
  
  Also: Uber's Ludwig is an Open Source Framework for Low-Code Machine Learning; Understanding Machine Learning: The Free eBook; Best Machine Learning Youtube Videos Under 10 Minutes; The Most Important Fundamentals of PyTorch you Should Know

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• Top Stories, Jun 8-14: Easy Speech-to-Text with Python; Natural Language Processing with Python: The Free eBook - Jun 15, 2020.
  
  Also: Five Cognitive Biases In Data Science (And how to avoid them); Deploy a Machine Learning Pipeline to the Cloud Using a Docker Container; Naive Bayes Algorithm: Everything you need to know; The Best NLP with Deep Learning Course is Free

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• Top May Stories: The Best NLP with Deep Learning Course is Free - Jun 10, 2020.
  
  Also: How to Think Like a Data Scientist; Python For Everybody: The Free eBook; Automated Machine Learning: The Free eBook.

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• Top Stories, Jun 1-7: Don’t Democratize Data Science; Deep Learning for Coders with fastai and PyTorch: The Free eBook - Jun 8, 2020.
  
  Also: Deep Learning for Detecting Pneumonia from X-ray Images; From Languages to Information: Another Great NLP Course from Stanford; Skills to Build for Data Engineering; If you had to start statistics all over again, where would you start?

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• Top Stories, May 25-31: Python For Everybody: The Free eBook; Interactive Machine Learning Experiments - Jun 1, 2020.
  
  Also: Dataset Splitting Best Practices in Python; 10 Useful Machine Learning Practices For Python Developers; How to Think Like a Data Scientist or Data Analyst; The Best NLP with Deep Learning Course is Free

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• Top Stories, May 18-24: The Best NLP with Deep Learning Course is Free - May 25, 2020.
  
  Also: Automated Machine Learning: The Free eBook; Sparse Matrix Representation in Python; Build and deploy your first machine learning web app; Complex logic at breakneck speed: Try Julia for data science

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• Top Stories, May 11-17: Start Your Machine Learning Career in Quarantine; AI and Machine Learning for Healthcare - May 18, 2020.
  
  Also: Satellite Image Analysis with fast.ai for Disaster Recovery; Machine Learning in Power BI using PyCaret; Deep Learning: The Free eBook; 24 Best (and Free) Books To Understand Machine Learning

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• Top Stories, May 4-10: Deep Learning: The Free eBook; Beginners Learning Path for Machine Learning - May 11, 2020.
  
  Also: How use the Coronavirus crisis to kickstart your Data Science career; 5 Concepts You Should Know About Gradient Descent and Cost Function; Five Cool Python Libraries for Data Science; Natural Language Processing Recipes: Best Practices and Examples

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• Top April Stories: Mathematics for Machine Learning: The Free eBook; The Super Duper NLP Repo: 100 Ready-to-Run Colab Notebooks, - May 8, 2020.
  
  Also: Introducing MIDAS: A New Baseline for Anomaly Detection in Graphs; The Super Duper NLP Repo: 100 Ready-to-Run Colab Notebooks; Five Cool Python Libraries for Data Science.

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• Top Stories, Apr 27 – May 3: Five Cool Python Libraries for Data Science; Natural Language Processing Recipes: Best Practices and Examples - May 4, 2020.
  
  Also: Coronavirus COVID-19 Genome Analysis using Biopython; LSTM for time series prediction; A Concise Course in Statistical Inference: The Free eBook; Exploring the Impact of Geographic Information Systems

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• Top Stories, Apr 20-26: The Super Duper NLP Repo; Free High-Quality Machine Learning & Data Science Books & Courses - Apr 27, 2020.
  
  Also: Should Data Scientists Model COVID19 and other Biological Events; 5 Papers on CNNs Every Data Scientist Should Read; 24 Best (and Free) Books To Understand Machine Learning; Mathematics for Machine Learning: The Free eBook; Find Your Perfect Fit: A Quick Guide for Job Roles in the Data World

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• Top Stories, Apr 13-19: Can Java Be Used for Machine Learning and Data Science?; How Deep Learning is Accelerating Drug Discovery in Pharmaceuticals - Apr 20, 2020.
  
  Also: Peer Reviewing Data Science Projects; Visualizing Decision Trees with Python (Scikit-learn, Graphviz, Matplotlib); Can Java Be Used for Machine Learning and Data Science?; Mathematics for Machine Learning: The Free eBook; 24 Best (and Free) Books To Understand Machine Learning

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• Top Stories, Apr 6-12: Mathematics for Machine Learning: The Free eBook; 10 Must-read Machine Learning Articles (March 2020) - Apr 13, 2020.
  
  Also: Top KDnuggets tweets, Apr 01-07: How to change global policy on #coronavirus; 5 Ways Data Scientists Can Help Respond to COVID-19 and 5 Actions to Avoid; How to Do Hyperparameter Tuning on Any Python Script in 3 Easy Steps; COVID-19 Visualized: The power of effective visualizations for pandemic storytelling

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• Top March stories: 24 Best (and Free) Books To Understand Machine Learning; COVID-19 Visualized: The power of effective visualizations; 20 AI, DS, ML terms you need to know - Apr 9, 2020.
  
  Also: 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 2); Linear to Logistic Regression, Explained Step by Step.

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• Top Stories, Mar 30 – Apr 5: COVID-19 Visualized: The power of effective visualizations for pandemic storytelling; Introducing MIDAS: A New Baseline for Anomaly Detection in Graphs - Apr 6, 2020.
  
  Also: How (not) to use Machine Learning for time series forecasting: The sequel; Best Free Epidemiology Courses for Data Scientists; Research into 1,001 Data Scientist LinkedIn Profiles, the latest; How (not) to use Machine Learning for time series forecasting: The sequel; Stop Hurting Your Pandas!

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• Top Stories, Mar 23-29: 24 Best (and Free) Books To Understand Machine Learning; COVID-19 Visualized: The power of effective visualizations for pandemic storytelling - Mar 30, 2020.
  
  Also: Coronavirus Data and Poll Analysis – yes, there is hope, if we act now; Making sense of ensemble learning techniques; Nine lessons learned during my first year as a Data Scientist; Deep Learning Breakthrough: a sub-linear deep learning algorithm that does not need a GPU?

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• Top Stories, Mar 16-22: 24 Best (and Free) Books To Understand Machine Learning - Mar 23, 2020.
  
  Also: Time Series Classification Synthetic vs Real Financial Time Series; Nine lessons learned during my first year as a Data Scientist; What is the most effective policy response to the new coronavirus pandemic?; Nine lessons learned during my first year as a Data Scientist; Five Interesting Data Engineering Projects

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• Top Stories, Mar 9-15: New Poll: Coronavirus impact on Data Science community; Covid-19, your community, and you — a data science perspective - Mar 16, 2020.
  
  Also: 50 Must-Read Free Books For Every Data Scientist in 2020; Decision Boundary for a Series of Machine Learning Models; 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 2)

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• Top Stories, Mar 2-8: 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 2) - Mar 9, 2020.
  
  Also: Linear to Logistic Regression, Explained Step by Step; Trends in Machine Learning in 2020; Tokenization and Text Data Preparation with TensorFlow & Keras; The Death of Data Scientists — will AutoML replace them?

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• Top February Stories: The Death of Data Scientists – will AutoML replace them? - Mar 6, 2020.
  
  Also: Learning from 3 big Data Science career mistakes; Leaders, Changes, and Trends in Gartner 2020 MQ Data Science and Machine Learning Platforms; Why Did I Reject a Data Scientist Job; Free Mathematics Courses for Data Science & Machine Learning.

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• Top Stories, Feb 24 – Mar 1: Learning from 3 big Data Science career mistakes; Free Mathematics Courses for Data Science & Machine Learning - Mar 2, 2020.
  
  Also: The Death of Data Scientists — will AutoML replace them?; Probability Distributions in Data Science; The Big Bad NLP Database: Access Nearly 300 Datasets;; Leaders, Changes, and Trends in Gartner 2020 Magic Quadrant for Data Science and Machine Learning Platforms; New Poll: When Will AutoML Replace Data Scientists (if ever)?

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• Top Stories, Feb 17-23: The Death of Data Scientists will AutoML replace them? - Feb 24, 2020.
  
  Also: 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 1); Audio Data Analysis Using Deep Learning with Python (Part 1); Hand labeling is the past. The future is #NoLabel AI; Googles Data Science Interview Brain Teasers

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• Top Stories, Feb 10-16: Why Did I Reject a Data Scientist Job?; Fourier Transformation for a Data Scientist - Feb 17, 2020.
  
  Also: Math for Programmers – your guide for solving math problems in code; What Does it Mean to Deploy a Machine Learning Model?; Deep Neural Networks; Easy Image Dataset Augmentation with TensorFlow; Intent Recognition with BERT using Keras and TensorFlow 2

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• Top January Stories: How to land a Data Scientist job at your dream company; I wanna be a data scientist, but … how? - Feb 11, 2020.
  
  Also: The Book to Start You on Machine Learning; Top 5 must-have Data Science skills for 2020.

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• Top Stories, Jan 27 – Feb 2: How to land a Data Scientist job at your dream company; How to Optimize Your Jupyter Notebook - Feb 3, 2020.
  
  Also: Data Validation for Machine Learning; OpenAI is Adopting PyTorch… They Aren’t Alone; I wanna be a data scientist, but how?; Top 10 AI, Machine Learning Research Articles to know; Google Dataset Search Provides Access to 25 Million Datasets

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• Top Stories, Jan 20-26: I wanna be a data scientist, but how? - Jan 27, 2020.
  
  Also: Microsoft Introduces Project Petridish to Find the Best Neural Network for Your Problem; 10 Python String Processing Tips & Tricks; Random Forest — A Powerful Ensemble Learning Algorithm; Top 10 Technology Trends for 2020; The Book to Start You on Machine Learning

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• Top Stories, Jan 13-19: Math for Programmers!; Decision Tree Algorithm, Explained - Jan 20, 2020.
  
  Also: Top 9 Mobile Apps for Learning and Practicing Data Science; Classify A Rare Event Using 5 Machine Learning Algorithms; The Future of Machine Learning; The Book to Start You on Machine Learning

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• Top Stories, Jan 6-12: Top 5 must-have Data Science skills for 2020; 7 Resources to Becoming a Data Engineer - Jan 13, 2020.
  
  Also: The Book to Start You on Machine Learning; An Introductory Guide to NLP for Data Scientists with 7 Common Techniques; A Comprehensive Guide to Natural Language Generation; The Book to Start You on Machine Learning; 10 Python Tips and Tricks You Should Learn Today

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• Top December Stories: What is a Data Scientist Worth? AI, ML, DS, DL Research Main Developments and Key Trends - Jan 10, 2020.
  
  Also: Google's New Explainable AI Service; 10 Free Top Notch Machine Learning Courses.

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• Top Stories, Dec 30 – Jan 5: How To Ultralearn Data Science; Automated Machine Learning: How do teams work together on an AutoML project? - Jan 6, 2020.
  
  Also: Predict Electricity Consumption Using Time Series Analysis; What is the most important question for Data Science (and Digital Transformation); Why Python is One of the Most Preferred Languages for Data Science?; What is a Data Scientist Worth?; How to Speed up Pandas by 4x with one line of code

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• Top Stories, Dec 16-29: What is a Data Scientist Worth?; Google’s New Explainable AI Service - Dec 30, 2019.
  
  Also: Let’s Build an Intelligent Chatbot; 10 Best and Free Machine Learning Courses, Online; Build Pipelines with Pandas Using pdpipe; Alternative Cloud Hosted Data Science Environments

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• Top 2019 Stories: Top 10 Technology Trends of 2019; How to select rows and columns in Pandas - Dec 17, 2019.
  
  Also: Your AI skills are worth less than you think; Another 10 Free Must-See Courses for Machine Learning and Data Science.

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• Top Stories, Dec 9-15: Machine Learning & Data Science Research Main Developments, Key Trends; Build Pipelines with Pandas Using pdpipe - Dec 16, 2019.
  
  Also: Plotnine: Python Alternative to ggplot2; AI, Analytics, Machine Learning, Data Science, Deep Learning Technology Main Developments in 2019 and Key Trends for 2020; Moving Predictive Maintenance from Theory to Practice; 10 Free Top Notch Machine Learning Courses; Math for Programmers!

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• Top November Stories: How to Speed up Pandas by 4x with one line of code - Dec 10, 2019.
  
  Also: 10 Free Must-read Books on AI; Data Science for Managers: Programming Languages; The Complete Data Science LinkedIn Profile Guide.

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• Top Stories, Dec 2-8: How to Speed up Pandas by 4x with one line of code; 10 Free Top Notch Machine Learning Courses - Dec 9, 2019.
  
  Also: Data Science Curriculum Roadmap; Enabling the Deep Learning Revolution; The Essential Toolbox for Data Cleaning; A Non-Technical Reading List for Data Science; The Future of Careers in Data Science & Analysis

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• Top Stories, Nov 25 – Dec 1: How to Speed up Pandas by 4x with one line of code; Open Source Projects by Google, Uber and Facebook for Data Science and AI - Dec 2, 2019.
  
  Also: Getting Started with Automated Text Summarization; A Doomed Marriage of Machine Learning and Agile; The Future of Careers in Data Science & Analysis; The Future of Careers in Data Science & Analysis; Can Neural Networks Develop Attention? Google Thinks they Can

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• Top Stories, Nov 18-24: How to Speed up Pandas by 4x with one line of code; Python, Selenium & Google for Geocoding Automation: Free and Paid - Nov 25, 2019.
  
  Also: Automated Machine Learning Project Implementation Complexities; Text Encoding: A Review; The Notebook Anti-Pattern; Data Science for Managers: Programming Languages; 10 Free Must-read Books on AI

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• Top Stories, Nov 11-17: How to Speed up Pandas by 4x with one line of code - Nov 18, 2019.
  
  Also: The Complete Data Science LinkedIn Profile Guide; How Data Analytics Can Assist in Fraud Detection; Research Guide for Depth Estimation with Deep Learning; 10 Free Must-read Books on AI; Beginners Guide to the Three Types of Machine Learning

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• Top Stories, Nov 4-10: 10 Free Must-read Books on AI - Nov 11, 2019.
  
  Also: Understanding Boxplots; Probability Learning: Maximum Likelihood; Designing Your Neural Networks; Facebook Has Been Quietly Open Sourcing Some Amazing Deep Learning Capabilities for PyTorch; 5 Statistical Traps Data Scientists Should Avoid

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• Top October Stories: How to Become a (Good) Data Scientist; Everything a Data Scientist Should Know About Data Management; The Last SQL Guide for Data Analysis - Nov 8, 2019.
  
  Also A European Approach to Master's Degrees in Data Science; How YouTube is Recommending Your Next Video

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• Top Stories, Oct 28 – Nov 3: 5 Statistical Traps Data Scientists Should Avoid; Top Machine Learning Software Tools for Developers - Nov 4, 2019.
  
  Also: Why is Machine Learning Deployment Hard?; Data Sources 101; 5 Statistical Traps Data Scientists Should Avoid; Everything a Data Scientist Should Know About Data Management; How to Become a (Good) Data Scientist — Beginner Guide

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• Top Stories, Oct 21-27: Everything a Data Scientist Should Know About Data Management; How YouTube is Recommending Your Next Video - Oct 28, 2019.
  
  Also: Introduction to Natural Language Processing (NLP); Anomaly Detection, A Key Task for AI and Machine Learning, Explained; How to Become a (Good) Data Scientist — Beginner Guide

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• Top Stories, Oct 14-20: How to Become a (Good) Data Scientist Beginner Guide - Oct 21, 2019.
  
  Also: The 5 Classification Evaluation Metrics Every Data Scientist Must Know; Artificial Intelligence: Salaries Heading Skyward; Writing Your First Neural Net in Less Than 30 Lines of Code with Keras; How to select rows and columns in Pandas using [ ], .loc, iloc, .at and .iat; The Last SQL Guide for Data Analysis You'll Ever Need

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• Top Stories, Oct 7-13: 10 Free Top Notch Natural Language Processing Courses; The Last SQL Guide for Data Analysis You’ll Ever Need - Oct 14, 2019.
  
  Also: Activation maps for deep learning models in a few lines of code; The 4 Quadrants of Data Science Skills and 7 Principles for Creating a Viral Data Visualization; OpenAI Tried to Train AI Agents to Play Hide-And-Seek but Instead They Were Shocked by What They Learned; 10 Great Python Resources for Aspiring Data Scientists

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• Top September Stories: I wasn’t getting hired as a Data Scientist. So I sought data on who is. - Oct 8, 2019.
  
  Also: 10 Great Python Resources for Aspiring Data Scientists; Python Libraries for Interpretable Machine Learning.

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• Top Stories, Sep 30 – Oct 6: The Last SQL Guide for Data Analysis You’ll Ever Need; Know Your Data: Part 1 - Oct 7, 2019.
  
  Also: How AI will transform healthcare (and can it fix the US healthcare system?); Choosing the Right Clustering Algorithm for your Dataset; DeepMind Has Quietly Open Sourced Three New Impressive Reinforcement Learning Frameworks; A European Approach to Masters Degrees in Data Science; The Future of Analytics and Data Science

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• Top Stories, Sep 23-29: The Future of Analytics and Data Science; 5 Famous Deep Learning Courses/Schools of 2019 - Sep 30, 2019.
  
  Also: 12 Deep Learning Researchers and Leaders; Natural Language in Python using spaCy: An Introduction; A Single Function to Streamline Image Classification with Keras; Which Data Science Skills are core and which are hot/emerging ones?; 6 bits of advice for Data Scientists

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• Top Stories, Sep 16-22: Which Data Science Skills are core and which are hot/emerging ones? - Sep 23, 2019.
  
  Also: Explore the world of Bioinformatics with Machine Learning; My journey path from a Software Engineer to BI Specialist to a Data Scientist; 5 Beginner Friendly Steps to Learn Machine Learning and Data Science with Python; 10 Great Python Resources for Aspiring Data Scientists

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• Top Stories, Sep 9-15: 10 Great Python Resources for Aspiring Data Scientists - Sep 16, 2019.
  
  Also: The 5 Graph Algorithms That Data Scientists Should Know; Many Heads Are Better Than One: The Case For Ensemble Learning; BERT is changing the NLP landscape; I wasn't getting hired as a Data Scientist; There is No Free Lunch in Data Science

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• Top August Stories: How to Become More Marketable as a Data Scientist - Sep 10, 2019.
  
  Also: Top Handy SQL Features for Data Scientists; 12 NLP Researchers, Practitioners & Innovators You Should Be Following; Knowing Your Neighbours: Machine Learning on Graphs

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• Top Stories, Sep 2-8: I wasn’t getting hired as a Data Scientist. So I sought data on who is. - Sep 9, 2019.
  
  Also: Python Libraries for Interpretable Machine Learning; TensorFlow vs PyTorch vs Keras for NLP; Advice on building a machine learning career and reading research papers by Prof. Andrew Ng; Object-oriented programming for data scientists: Build your ML estimator

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• Top Stories, Aug 26 – Sep 1: Object-oriented programming for data scientists; Why Data Visualization Is The Most Important Skill in a Data Analyst Arsenal - Sep 2, 2019.
  
  Also: Types of Bias in Machine Learning; Deep Learning Next Step: Transformers and Attention Mechanism; New Poll: Data Science Skills; R Users Salaries from the 2019 Stackoverflow Survey; How to Sell Your Boss on the Need for Data Analytics

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• Top Stories, Aug 19-25: Top Handy SQL Features for Data Scientists; Nothing but NumPy: Understanding & Creating Neural Networks with Computational Graphs from Scratch - Aug 26, 2019.
  
  Also: Deep Learning for NLP: Creating a Chatbot with Keras!; Understanding Decision Trees for Classification in Python; How to Become More Marketable as a Data Scientist; Is Kaggle Learn a Faster Data Science Education?

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• Top Stories, Aug 12-18: How to Become More Marketable as a Data Scientist; 12 NLP Researchers, Practitioners & Innovators You Should Be Following - Aug 19, 2019.
  
  Also: How to Become More Marketable as a Data Scientist; 6 Key Concepts in Andrew Ng’s “Machine Learning Yearning”; Understanding Cancer using Machine Learning; Command Line Basics Every Data Scientist Should Know

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• Top July Stories: The Death of Big Data and the Emergence of the Multi-Cloud Era - Aug 14, 2019.
  
  Also: Top 13 Skills To Become a Rockstar Data Scientist, Top 10 Data Science Leaders You Should Follow; What's wrong with the approach to Data Science?

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• Top Stories, Aug 5-11: Knowing Your Neighbours: Machine Learning on Graphs; What is Benford’s Law and why is it important for data science? - Aug 12, 2019.
  
  Also: Deep Learning for NLP: ANNs, RNNs and LSTMs explained!; Machine Learning is Happening Now: A Survey of Organizational Adoption, Implementation, and Investment; 25 Tricks for Pandas; Getting Started with Data Science; Data Science: Scientific Discipline or Business Process?

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• Top Stories, Jul 29 – Aug 4: Top 10 Best Podcasts on AI, Analytics, Data Science, Machine Learning; What 70% of Data Science Learners Do Wrong - Aug 5, 2019.
  
  Also: GPU Accelerated Data Analytics & Machine Learning; Understanding Tensor Processing Units; Top 13 Skills To Become a Rockstar Data Scientist; Five Command Line Tools for Data Science; Ten more random useful things in R you may not know about

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• Top Stories, Jul 22-28: Top 13 Skills To Become a Rockstar Data Scientist; This New Google Technique Help Us Understand How Neural Networks are Thinking - Jul 29, 2019.
  
  Also: Convolutional Neural Networks: A Python Tutorial Using TensorFlow and Keras; Fantastic Four of Data Science Project Preparation; The Death of Big Data and the Emergence of the Multi-Cloud Era; The title CDO started out as a joke

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• Top Stories, Jul 15-21: The Death of Big Data and the Emergence of the Multi-Cloud Era; Bayesian deep learning and near-term quantum computers - Jul 22, 2019.
  
  Also: Dealing with categorical features in machine learning; Computer Vision for Beginners: Part 1; Big Data for Insurance; A Summary of DeepMind's Protein Folding Upset at CASP13; The Hackathon Guide for Aspiring Data Scientists

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• Top Stories, Jul 8-14: The Death of Big Data and the Emergence of the Multi-Cloud Era; Training a Neural Network to Write Like Lovecraft - Jul 15, 2019.
  
  Also: What's wrong with the approach to Data Science?; Introducing Gen: MITs New Language That Wants to be the TensorFlow of Programmable Inference; Top 10 Data Science Leaders You Should Follow; 5 Probability Distributions Every Data Scientist Should Know; XGBoost and Random Forest with Bayesian Optimisation

  Tags: Top stories

• Top June Stories: 5 Useful Statistics Data Scientists Need to Know; 7 Steps to Mastering Intermediate Machine Learning with Python – 2019 Edition - Jul 12, 2019.
  
  Also: Data Science Jobs Report 2019: Python Way Up, TensorFlow Growing Rapidly, R Use Double SAS; If you're a developer transitioning into data science, here are your best resources.

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• Top Stories, Jul 1-7: 5 Probability Distributions Every Data Scientist Should Know; NLP vs. NLU: from Understanding a Language to Its Processing - Jul 8, 2019.
  
  Also: XLNet Outperforms BERT on Several NLP Tasks; How do you check the quality of your regression model in Python?; How Data Science Is Used Within the Film Industry; Whats the Machine Learning Engineering Job Like; 7 Steps to Mastering Data Preparation for Machine Learning with Python — 2019 Edition

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• Top Stories, Jun 24-30: Understanding Cloud Data Services; 7 Steps to Mastering Data Preparation for Machine Learning with Python — 2019 Edition - Jul 1, 2019.
  
  Also: How To Get Funding For AI Startups; Optimization with Python: How to make the most amount of money with the least amount of risk?; 5 Useful Statistics Data Scientists Need to Know; Data Science Jobs Report 2019: Python Way Up, TensorFlow Growing Rapidly, R Use Double SAS

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• Top Stories, Jun 17 – 23: Data Science Jobs Report 2019; Spark NLP: Getting Started With The World’s Most Widely Used NLP Library In The Enterprise - Jun 24, 2019.
  
  5 Useful Statistics Data Scientists Need to Know; How to Learn Python for Data Science the Right Way; The Machine Learning Puzzle, Explained; How to select rows and columns in Pandas using [ ], .loc, iloc, .at and .iat

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• Top Stories, Jun 10 – 16: Best resources for developers transitioning into data science; 5 Useful Statistics Data Scientists Need to Know - Jun 17, 2019.
  
  The Infinity Stones of Data Science; What you need to know about the Modern Open-Source Data Science ecosystem; Scalable Python Code with Pandas UDFs: A Data Science Application; Become a Pro at Pandas

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• Top May Stories: A Step-by-Step Guide to Transitioning your Career to Data Science; 7 Steps to Mastering SQL for Data Science – 2019 Edition - Jun 11, 2019.
  
  Also: The Third Wave Data Scientist; Python leads the 11 top Data Science, Machine Learning platforms: Trends and Analysis

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• Top Stories, Jun 3-9: 7 Steps to Mastering Intermediate Machine Learning with Python 2019 Edition; How to choose a visualization - Jun 10, 2019.
  
  A Step-by-Step Guide to Transitioning your Career to Data Science Part 1; Math for Programmers; PyViz: Simplifying the Data Visualisation Process in Python

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• Top Stories, May 27 – Jun 2: A Step-by-Step Guide to Transitioning your Career to Data Science – Part 1; Python leads the 11 top Data Science, Machine Learning platforms: Trends and Analysis - Jun 3, 2019.
  
  Understanding Backpropagation as Applied to LSTM; How the Lottery Ticket Hypothesis is Challenging Everything we Knew About Training Neural Networks; AI in the Family: how to teach machine learning to your kids

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• Top Stories, May 20-26: 7 Steps to Mastering SQL for Data Science; The Data Fabric for Machine Learning - May 27, 2019.
  
  Building a Computer Vision Model: Approaches and datasets; Your Guide to Natural Language Processing (NLP); Analyzing Tweets with NLP in Minutes with Spark, Optimus and Twint; The 3 Biggest Mistakes on Learning Data Science

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• Top Stories, May 13-19: 7 Steps to Mastering SQL for Data Science — 2019 Edition; Mathematical programming — Key Habit to Build Up for Advancing Data Science - May 20, 2019.
  
  Also: Machine Learning in Agriculture: Applications and Techniques; 60+ useful graph visualization libraries; How (not) to use Machine Learning for time series forecasting: Avoiding the pitfalls; The Third Wave Data Scientist; The 3 Biggest Mistakes on Learning Data Science

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• Top Stories, May 6-12: The Third Wave Data Scientist; The 3 Biggest Mistakes on Learning Data Science - May 13, 2019.
  
  Also: Data Scientist Best Job of the Year in USA; How (not) to use Machine Learning for time series forecasting: Avoiding the pitfalls; 2019 KDnuggets Poll: What software you used for Analytics, Data Mining, Data Science, Machine Learning projects in the past 12 months?; The most desired skill in data science; Please, explain. Interpretability of machine learning

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• Top April Stories: The most desired skill in data science; Top 10 Coding Mistakes Made by Data Scientists - May 10, 2019.
  
  Also: Another 10 Free Must-See Courses for Machine Learning and Data Science; How to Recognize a Good Data Scientist Job From a Bad One.

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• Top Stories, Apr 29 – May 5: The most desired skill in data science; Top Data Science and Machine Learning Methods Used in 2018, 2019 - May 6, 2019.
  
  Also: Normalization vs Standardization — Quantitative analysis; Build Your First Chatbot Using Python & NLTK; Which Deep Learning Framework is Growing Fastest?; Pandas DataFrame Indexing; XGBoost Algorithm: Long May She Reign

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• Top KDnuggets tweets, Apr 24–30: Another 10 Free Must-Read Books for Machine Learning and Data Science; Top #DataScience & #MachineLearning Methods Used in 2018/19 - May 1, 2019.
  
  Also: Data Visualization in Python: Matplotlib vs Seaborn; Data Science Project Flow for Startups; Pandas DataFrame Indexing; Best Data Visualization Techniques for small and large data; The most desired skill in #DataScience

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• Top Stories, Apr 22-28: The most desired skill in data science; How To Go Into Data Science: Ultimate Q&A for Aspiring Data Scientists - Apr 30, 2019.
  
  Artificial Intelligence 101 Cheatsheet; AI Supporting The Earth; Data Visualization in Python: Matplotlib vs Seaborn; 2019 Best Masters in Data Science and Analytics Online; Graduating in GANs: Going From Understanding Generative Adversarial Networks to Running Your Own

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• Top Stories, Apr 15-21: Data Visualization in Python: Matplotlib vs Seaborn; Data Science with Optimus Part 2: Setting your DataOps Environment - Apr 23, 2019.
  
  Also: Best Data Visualization Techniques for small and large data; K-Means Clustering: Unsupervised Learning for Recommender Systems; An Introduction on Time Series Forecasting with Simple Neural Networks & LSTM; The Rise of Generative Adversarial Networks

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• Top Stories, Apr 8-14: How to Recognize a Good Data Scientist Job From a Bad One; An Introduction on Time Series Forecasting with Simple Neural Networks & LSTM - Apr 16, 2019.
  
  Also: Which Data Science / Machine Learning methods and algorithms did you use in 2018/2019 for a real-world application?; Why Data Scientists Need To Work In Groups; Advice for New Data Scientists

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• Top March Stories: Another 10 Free Must-Read Books for Machine Learning and Data Science - Apr 15, 2019.
  
  Also: Artificial Neural Networks Optimization using Genetic Algorithm with Python; Who is a typical Data Scientist in 2019?

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• Top Stories, Apr 1-7: Top 10 Coding Mistakes Made by Data Scientists; Another 10 Free Must-See Courses for Machine Learning and Data Science - Apr 8, 2019.
  
  Also: 7 Qualities Your Big Data Visualization Tools Absolutely Must Have and 10 Tools That Have Them; Getting started with NLP using the PyTorch framework; Predict Age and Gender Using Convolutional Neural Network and OpenCV; Which Face is Real?

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• Top Stories, Mar 25-31: R vs Python for Data Visualization; The Deep Learning Toolset — An Overview - Apr 2, 2019.
  
  Also: Pedestrian Detection in Aerial Images Using RetinaNet; How to Choose the Right Chart Type; Explaining Random Forest (with Python Implementation); A Beginner's Guide to Linear Regression in Python with Scikit-Learn; The Four Levels of Analytics Maturity

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• Top Stories, Mar 18-24: Another 10 Free Must-Read Books for Machine Learning and Data Science; Artificial Neural Networks Optimization using Genetic Algorithm with Python - Mar 26, 2019.
  
  Also: 8 Reasons Why You Should Get a Microsoft Azure Certification; How To Work In Data Science, AI, Big Data; How to Train a Keras Model 20x Faster with a TPU for Free; Who is a typical Data Scientist in 2019?; My Best Tips for Agile Data Science Research

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• Top Stories, Mar 11-17: Who is a typical Data Scientist in 2019?; The Pareto Principle for Data Scientists - Mar 18, 2019.
  
  Also: Another 10 Free Must-Read Books for Machine Learning and Data Science; Building NLP Classifiers Cheaply With Transfer Learning and Weak Supervision; My favorite mind-blowing Machine Learning/AI breakthroughs; The 7 Myths of Data Anonymisation

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• Top Stories, Mar 4-10: Another 10 Free Must-Read Books for Machine Learning and Data Science; 19 Inspiring Women in AI, Big Data, Data Science, ML - Mar 12, 2019.
  
  Also: Neural Networks seem to follow a puzzlingly simple strategy to classify images; Neural Networks with Numpy - Intro for Absolute Beginners.

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• Top February Stories: Data Scientists: Why are they so expensive to hire? Artificial Neural Network Implementation using NumPy and Image Classification - Mar 7, 2019.
  
  Also: Gainers, Losers, and Trends in Gartner 2019 Magic Quadrant for Data Science and Machine Learning Platforms; The Essential Data Science Venn Diagram.

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• Top Stories, Feb 25 – Mar 3: Asking Great Questions as a Data Scientist; 4 Reasons Why Your Machine Learning Code is Probably Bad - Mar 5, 2019.
  
  Also: Deconstructing BERT: Distilling 6 Patterns from 100 Million Parameters; How to do Everything in Computer Vision; What no one will tell you about data science job applications; Python Data Science for Beginners

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• Top Stories, Feb 18-24: How to Setup a Python Environment for Machine Learning; Artificial Neural Network Implementation using NumPy - Feb 26, 2019.
  
  Also: Running R and Python in Jupyter; What are Some “Advanced” AI and Machine Learning Online Courses?; Python Data Science for Beginners; 6 Books About Open Data Every Data Scientist Should Read

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• Top Stories, Feb 11-17: Gainers, Losers, and Trends in Gartner 2019 Magic Quadrant; Scikit Learn: The Gold Standard of Python Machine Learning - Feb 18, 2019.
  
  Also: Learn How to Listen: One of the hardest parts of being a data scientist; Top 10 Data Science Use Cases in Telecom; The Best and Worst Data Visualizations of 2018; The Analytics Engineer – new role in the data team; A Quick Guide to Feature Engineering

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• Top January Stories: Your AI skills are worth less than you think - Feb 13, 2019.
  
  Also: The cold start problem: how to build your machine learning portfolio; 7 Steps to Mastering Basic Machine Learning with Python - 2019 Edition.

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• Top Stories, Feb 4-10: Data Scientists: Why are they so expensive to hire?; The Essential Data Science Venn Diagram - Feb 12, 2019.
  
  Also: Intuitive Visualization of Outlier Detection Methods; Understanding Gradient Boosting Machines; The Best and Worst Data Visualizations of 2018; Your AI skills are worth less than you think

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• Top Stories, Jan 28 – Feb 3: 7 Steps to Mastering Basic Machine Learning with Python — 2019 Edition; Your AI skills are worth less than you think - Feb 5, 2019.
  
  Also: Data Scientists: Why are they so expensive to hire?; Trending Deep Learning Github Repositories; The Algorithms Aren’t Biased, We Are; Five Ways Your Safety Depends on Machine Learning; Cracking the Data Scientist Interview

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• Top Stories, Jan 21-27: 2018’s Top 7 Python Libraries for Data Science and AI; Your AI skills are worth less than you think - Jan 29, 2019.
  
  Also: 2018's Top 7 R Packages for Data Science and AI; Data Science Project Flow for Startups; What were the most significant machine learning/AI advances in 2018?; How to go from Zero to Employment in Data Science; Logistic Regression: A Concise Technical Overview

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• Top Stories, Jan 14-20: How to go from Zero to Employment in Data Science; End To End Guide For Machine Learning Projects - Jan 22, 2019.
  
  Also: How to build an API for a machine learning model in 5 minutes using Flask; How to solve 90% of NLP problems: a step-by-step guide; Data Scientists Dilemma: The Cold Start Problem - Ten Machine Learning Examples; Ontology and Data Science; 9 Must-have skills you need to become a Data Scientist, updated

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• Top Stories, Jan 7-13: The Five Best Data Visualization Libraries; Modern Deep Learning Techniques Applied to NLP - Jan 15, 2019.
  
  Also: Top 10 Books on NLP and Text Analysis; Practical Apache Spark in 10 Minutes; The cold start problem: how to build your machine learning portfolio; Core Principles of Sustainable Data Science, Machine Learning and AI Product Development; 4 Myths of Big Data and 4 Ways to Improve with Deep Data

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• Top December Stories: Why You Shouldn’t be a Data Science Generalist - Jan 9, 2019.
  
  Also: Common mistakes when carrying out machine learning and data science; Learning Machine Learning vs Learning Data Science; Here are the most popular Python IDEs / Editors; 10 More Must-See Free Courses for Machine Learning and Data Science.

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• Top Stories, Dec 24 – Jan 6: The Essence of Machine Learning; Papers with Code: A Fantastic GitHub Resource for Machine Learning - Jan 8, 2019.
  
  Also: A Guide to Decision Trees for Machine Learning and Data Science; The cold start problem: how to build your machine learning portfolio; Comparison of the Top Speech Processing APIs; Synthetic Data Generation: A must-have skill for new data scientists; Approaches to Text Summarization: An Overview

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• Top Stories, Dec 17-23: Why You Shouldn’t be a Data Science Generalist; 10 More Must-See Free Courses for Machine Learning and Data Science - Dec 24, 2018.
  
  Also: Introduction to Statistics for Data Science; Top Python Libraries in 2018 in Data Science, Deep Learning, Machine Learning; Industry Predictions: AI, Machine Learning, Analytics & Data Science Main Developments in 2018 and Key Trends for 2019

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• Top Stories, Dec 10-16: Why You Shouldn’t be a Data Science Generalist; Machine Learning & AI Main Developments in 2018 and Key Trends for 2019 - Dec 17, 2018.
  
  Also: Learning Machine Learning vs Learning Data Science; Should you become a data scientist?; Learning Machine Learning vs Learning Data Science; Common mistakes when carrying out machine learning and data science; How Different are Conventional Programming and Machine Learning?

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• Top Stories of 2018: 9 Must-have skills you need to become a Data Scientist, updated; Python eats away at R: Top Software for Analytics, Data Science, Machine Learning - Dec 14, 2018.
  
  Also 5 Data Science Projects That Will Get You Hired in 2018; Top 20 Python AI and Machine Learning Open Source Projects; Neural network AI is simple. So... Stop pretending you are a genius.

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• Top November Stories: The Most in Demand Skills for Data Scientists; What is the Best Python IDE for Data Science? - Dec 11, 2018.
  
  Also: To get hired as a data scientist, don't follow the herd; 10 Free Must-See Courses for Machine Learning and Data Science.

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• Top Stories, Dec 3-9: Common mistakes when carrying out machine learning and data science; AI, Data Science, Analytics Main Developments in 2018 and Key Trends for 2019 - Dec 10, 2018.
  
  Also: Data Science Projects Employers Want To See: How To Show A Business Impact; The Machine Learning Project Checklist; Here are the most popular Python IDEs / Editors; The Machine Learning Project Checklist

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• Top Stories, Nov 26 – Dec 2: Deep Learning Cheat Sheets; A Complete Guide to Choosing the Best Machine Learning Course - Dec 3, 2018.
  
  Also: A Complete Guide to Choosing the Best Machine Learning Course; My secret sauce to be in top 2% of a Kaggle competition; Deep Learning for the Masses ( and The Semantic Layer); What is the Best Python IDE for Data Science?; 9 Must-have skills you need to become a Data Scientist, updated

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• Top Stories, Nov 19-25: What is the Best Python IDE for Data Science?; Intro to Data Science for Managers - Nov 26, 2018.
  
  Also: An Introduction to AI; The Big Data Game Board; 6 Goals Every Wannabe Data Scientist Should Make for 2019; 10 Free Must-See Courses for Machine Learning and Data Science; 9 Must-have skills you need to become a Data Scientist, updated

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• Top Stories, Nov 12-18: What is the Best Python IDE for Data Science?; To get hired as a data scientist, don’t follow the herd - Nov 19, 2018.
  
  Also: The 5 Basic Statistics Concepts Data Scientists Need to Know; Mastering The New Generation of Gradient Boosting; The Most in Demand Skills for Data Scientists; Mastering The New Generation of Gradient Boosting; Top 10 Python Data Science Libraries

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• Top Stories, Nov 5-11: The Most in Demand Skills for Data Scientists; 10 Free Must-See Courses for Machine Learning and Data Science - Nov 12, 2018.
  
  Also: What does a data scientist REALLY look like? Introduction to PyTorch for Deep Learning

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• Top October Stories: 9 Must-have skills you need to become a Data Scientist, updated; 10 Best Mobile Apps for Data Scientist / Data Analysts - Nov 9, 2018.
  
  Also: How To Learn Data Science If You're Broke; Graphs Are The Next Frontier In Data Science; BIG, small or Right Data: Which is the proper focus?

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• Top Stories, Oct 29 – Nov 4: The Most in Demand Skills for Data Scientists; How Machines Understand Our Language - Nov 5, 2018.
  
  Also: Introduction to Deep Learning with Keras; How Data Science Is Improving Higher Education; 9 Must-have skills you need to become a Data Scientist, updated; Data Representation for Natural Language Processing Tasks; Top 13 Python Deep Learning Libraries

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• Top Stories, Oct 22-28: 9 Must-have skills you need to become a Data Scientist, updated; Named Entity Recognition and Classification with Scikit-Learn - Oct 29, 2018.
  
  Also: SQL, Python, & R in One Platform; Generative Adversarial Networks – Paper Reading Road Map; Notes on Feature Preprocessing: The What, the Why, and the How; Graphs Are The Next Frontier In Data Science; 10 Best Mobile Apps for Data Scientist / Data Analysts

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• Top Stories, Oct 15-21: Graphs Are The Next Frontier In Data Science; The Main Approaches to Natural Language Processing Tasks - Oct 22, 2018.
  
  Also: GitHub Python Data Science Spotlight; The Intuitions Behind Bayesian Optimization with Gaussian Processes; 10 Best Mobile Apps for Data Scientist / Data Analysts; Apache Spark Introduction for Beginners

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• Top Stories, Oct 8-14: 10 Best Mobile Apps for Data Scientist / Data Analysts; BIG, small or Right Data: Which is the proper focus? - Oct 15, 2018.
  
  Also: How To Learn Data Science If You’re Broke; Top 8 Python Machine Learning Libraries; 9 Must-have skills you need to become a Data Scientist, updated; SQL, Python, & R: All in One Platform; Using Confusion Matrices to Quantify the Cost of Being Wrong

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• Top September Stories: Essential Math for Data Science: Why and How; Machine Learning Cheat Sheets - Oct 10, 2018.
  
  Also: Journey to Machine Learning - 100 Days of ML Code; How many data scientists are there and is there a shortage?

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• Top Stories, Oct 1-7: Machine Learning Cheat Sheets; How to Create a Simple Neural Network in Python - Oct 8, 2018.
  
  Also: Recent Advances for a Better Understanding of Deep Learning; Basic Image Data Analysis Using Python – Part 4; A Concise Explanation of Learning Algorithms with the Mitchell Paradigm; Essential Math for Data Science: Why and How

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• Top Stories, Sep 24-30: Machine Learning Cheat Sheets; Learning the Mathematics of Machine Learning - Oct 1, 2018.
  
  Also: Math for Machine Learning; Introducing Path Analysis Using R; Introduction to Deep Learning; Essential Math for Data Science: Why and How; 6 Steps To Write Any Machine Learning Algorithm From Scratch: Perceptron Case Study

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• Top Stories, Sep 17-23: How many data scientists are there and is there a shortage?; You Aren’t So Smart: Cognitive Biases are Making Sure of It - Sep 24, 2018.
  
  Also: 6 Steps To Write Any Machine Learning Algorithm From Scratch: Perceptron Case Study; A Winning Game Plan For Building Your Data Science Team; Machine Learning Cheat Sheets; Essential Math for Data Science: Why and How

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• Top Stories, Sep 10-16: Essential Math for Data Science: Why and How; Machine Learning Cheat Sheets - Sep 17, 2018.
  
  Also: Hadoop for Beginners; Object Detection and Image Classification with YOLO; Journey to Machine Learning 100 Days of ML Code; Data Visualization Cheat Sheet; Neural Networks and Deep Learning: A Textbook

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