Tag: Top stories (376)

Top Stories, Jan 8-14: Top 10 TED Talks for Data Scientists and Machine Learning Engineers; The Art of Learning Data Science - Jan 15, 2018.

Also: How Docker Can Help You Become A More Effective Data Scientist; Regularization in Machine Learning; Democratizing Artificial Intelligence, Deep Learning, Machine Learning with Dell EMC Ready Solutions; Quantum Machine Learning: An Overview

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Top December Stories: Computer Vision by Andrew Ng – 11 Lessons Learned; Top Data Science and Machine Learning Methods Used in 2017 - Jan 9, 2018.

Also: How Much Mathematics Does an IT Engineer Need to Learn to Get Into Data Science? Data Science, Machine Learning: Main Developments in 2017 and Key Trends in 2018.

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Top Stories, Jan 1-7: Docker for Data Science; Quantum Machine Learning: An Overview - Jan 8, 2018.

Also: Computer Vision by Andrew Ng – 11 Lessons Learned; How to build a Successful Advanced Analytics Department; Docker for Data Science; Top 10 Machine Learning Algorithms for Beginners

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Top Stories, Dec 18-31: How Much Mathematics Does an IT Engineer Need to Learn to Get Into Data Science?; Computer Vision by Andrew Ng – 11 Lessons Learned - Jan 3, 2018.

Also: 70 Amazing Free Data Sources You Should Know; Industry Predictions: Main AI, Big Data, Data Science Developments in 2017 and Trends for 2018; Can I Become a Data Scientist: Research into 1,001 Data Scientist Profiles; Yet Another Day in the Life of a Data Scientist

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Top Stories of 2017: 10 Free Must-Read Books for Machine Learning and Data Science; Python overtakes R, becomes the leader in Data Science, Machine Learning platforms - Dec 21, 2017.

Also Top 10 Machine Learning Algorithms for Beginners; 30 Essential Data Science, Machine Learning & Deep Learning Cheat Sheets.

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Top Stories, Dec 11-17: Data Science, Machine Learning: Main Developments in 2017 and Key Trends in 2018; Top Data Science and Machine Learning Methods Used in 2017 - Dec 18, 2017.

Also: Another Day in the Life of a Data Scientist; The 10 Deep Learning Methods AI Practitioners Need to Apply; Machine Learning & Artificial Intelligence: Main Developments in 2017 and Key Trends in 2018; Top 10 Machine Learning Algorithms for Beginners

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Top Stories, Dec 4-10: Using Deep Learning to Solve Real World Problems; Big Data: Main Developments in 2017 and Key Trends in 2018 - Dec 11, 2017.

Also: What is a Bayesian Neural Network?; Today I Built a Neural Network During My Lunch Break with Keras; 4 Common Data Fallacies That You Need To Know; Top 10 Machine Learning Algorithms for Beginners; The 10 Statistical Techniques Data Scientists Need to Master

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Top November Stories: The 10 Statistical Techniques Data Scientists Need to Master - Dec 7, 2017.

Also: Best Online Masters in Data Science and Analytics - a comprehensive, unbiased survey; Deep Learning Specialization by Andrew Ng - 21 Lessons Learned; Machine Learning Algorithms: Which One to Choose for Your Problem; Want to know how Deep Learning works? Here's a quick guide

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Top Stories, Nov 27-Dec 3: Embracing Vectorization in Data Science; Understanding Deep Convolutional Neural Networks - Dec 4, 2017.

Also: How To Unit Test Machine Learning Code; Evolutionary Algorithms for Feature Selection; A General Approach to Preprocessing Text Data; The 10 Statistical Techniques Data Scientists Need to Master; Deep Learning Specialization by Andrew Ng - 21 Lessons Learned

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Top Stories, Nov 20-26: Deep Learning Specialization by Andrew Ng – 21 Lessons Learned; A Framework for Approaching Textual Data Science Tasks - Nov 27, 2017.

Also: Estimating an Optimal Learning Rate For a Deep Neural Network; Automated Feature Engineering for Time Series Data; How (and Why) to Create a Good Validation Set; Building a Wikipedia Text Corpus for Natural Language Processing; The 10 Statistical Techniques Data Scientists Need to Master

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Top Stories, Nov 13-19: The 10 Statistical Techniques Data Scientists Need to Master; Best Online Masters in Data Science and Analytics – a comprehensive, unbiased survey - Nov 20, 2017.

Also: A Day in the Life of a Data Scientist; Top 10 Videos on Deep Learning in Python; 8 Ways to Improve Your Data Science Skills in 2 Years; Machine Learning Algorithms: Which One to Choose for Your Problem; Top 10 Machine Learning Algorithms for Beginners

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Top Stories, Nov 6-12: When Will Demand for Data Scientists/Machine Learning Experts Peak?; Interpreting Machine Learning Models: An Overview - Nov 13, 2017.

Also: TensorFlow: What Parameters to Optimize?; 7 Super Simple Steps From Idea To Successful Data Science Project; Tips for Getting Started with Text Mining in R and Python; Top 10 Machine Learning Algorithms for Beginners

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Top October Stories: Top 10 Machine Learning Algorithms for Beginners - Nov 8, 2017.

Also: Understanding Machine Learning Algorithms; Want to Become a Data Scientist? Read This Interview First; 6 Books Every Data Scientist Should Keep Nearby.

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Top Stories, Oct 30-Nov 5: 6 Books Every Data Scientist Should Keep Nearby; Want to know how Deep Learning works? Here’s a quick guide for everyone. - Nov 6, 2017.

Also: Advice For New and Junior Data Scientists; 7 Steps to Mastering Deep Learning with Keras; Getting Started with Machine Learning in One Hour!; Top 10 Machine Learning Algorithms for Beginners

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Top Stories, Oct 23-29: Ranking Popular Deep Learning Libraries; TensorFlow: Building Feed-Forward Neural Networks Step-by-Step - Oct 30, 2017.

Also: XGBoost: A Concise Technical Overview; Top 10 Machine Learning with R Videos; Neural Networks, Step 1: Where to Begin with Neural Nets & Deep Learning; Top 10 Machine Learning Algorithms for Beginners; 7 Types of Artificial Neural Networks for Natural Language Processing

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Top Stories, Oct 16-22: Top 10 Machine Learning Algorithms for Beginners; How LinkedIn Makes Personalized Recommendations - Oct 23, 2017.

Also: 7 Types of Artificial Neural Networks for Natural Language Processing; 7 Techniques to Visualize Geospatial Data; Want to Become a Data Scientist? Read This Interview First; Random Forests(r), Explained; 5 Free Resources for Furthering Your Understanding of Deep Learning

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Top Stories, Oct 9-15: Want to Become a Data Scientist? Read This Interview First; An Overview of 3 Popular Courses on Deep Learning - Oct 16, 2017.

Also: A Quick Guide to Fake News Detection on Social Media; How I started with learning AI in the last 2 months; Tidyverse, an opinionated Data Science Toolbox in R from Hadley Wickham; Understanding Machine Learning Algorithms; 30 Essential Data Science, Machine Learning & Deep Learning Cheat Sheets

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Top Stories, Oct 2-8: Understanding Machine Learning Algorithms; XGBoost, a Top Machine Learning Method on Kaggle, Explained - Oct 9, 2017.

Also: Using Machine Learning to Predict and Explain Employee Attrition; Data Science - The need for a Systems Engineering approach; Deep Learning for Object Detection: A Comprehensive Review; 30 Essential Data Science, Machine Learning & Deep Learning Cheat Sheets

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Top September Stories: 30 Essential Data Science, Machine Learning & Deep Learning Cheat Sheets - Oct 6, 2017.

Also: 277 Data Science Key Terms, Explained; I built a chatbot in 2 hours and this is what I learned; Data Science and the Imposter Syndrome

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Top Stories, Sep 25-Oct 1: Introduction to Blockchains for Big Data; Top 10 Active Big Data, Data Science, Machine Learning LinkedIn Influencers - Oct 2, 2017.

Also: 10 Things Everyone Should Know About Machine Learning; Top 10 Videos on Machine Learning in Finance; Machine Learning Reveals 9 Elements of Deal-Closing Sales; 30 Essential Data Science, Machine Learning & Deep Learning Cheat Sheets

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Top Stories, Sep 18-24: Essential Data Science & Machine Learning Cheat Sheets; How To Become a 10x Data Scientist - Sep 25, 2017.

30 Essential Data Science, Machine Learning & Deep Learning Cheat Sheets; How To Become a 10x Data Scientist; 5 Machine Learning Projects You Can No Longer Overlook – Episode VI; Ensemble Learning to Improve Machine Learning Results; Putting Machine Learning in Production

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Top Stories, Sep 11-17: Python vs R – Who Is Really Ahead in Data Science, Machine Learning?; Data Science and the Imposter Syndrome - Sep 18, 2017.

Also: New-Age Machine Learning Algorithms in Retail Lending; Top 10 Machine Learning Use Cases: Part 2; Python vs R for Artificial Intelligence, Machine Learning, and Data Science; Python overtakes R, becomes the leader in Data Science, Machine Learning platforms

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Top Stories, Sep 4-10: Putting the “Science” Back in Data Science; A Vision for Making Deep Learning Simple - Sep 11, 2017.

Also: Python overtakes R, becomes the leader in Data Science, Machine Learning platforms; I built a chatbot in 2 hours and this is what I learned; Closing the Insights-to-Action Gap; Are Data Lakes Fake News?; Visualizing Cross-validation Code

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Top August Stories: Python overtakes R, becomes the leader in Data Science, Machine Learning platforms - Sep 6, 2017.

Also 42 Steps to Mastering Data Science; Deep Learning is not the AI future; Data Science Primer; The Rise of GPU Databases; What AI Can and cannot do.

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Top Stories, Aug 28-Sep 3: Python Overtakes R in Data Science, Machine Learning; 277 Data Science Key Terms - Sep 4, 2017.

Also: How to Become a Data Scientist: The Definitive Guide; Top 10 Machine Learning Use Cases; Vital Statistics You Never Learned… Because They’re Never Taught; Deep Learning is not the AI future; 42 Steps to Mastering Data Science

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Top Stories, Aug 21-27: 42 Steps to Mastering Data Science; Deep Learning is not the AI future - Aug 28, 2017.

Also: 37 Reasons why your Neural Network is not working; Machine Learning vs. Statistics: The Texas Death Match of Data Science; Understanding overfitting: an inaccurate meme in Machine Learning; Recommendation System Algorithms: An Overview; The Ultimate Guide to Basic Data Cleaning

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Top Stories, Aug 14-20: The Rise of GPU Databases; A New Beginning to Deep Learning - Aug 21, 2017.

Also: Data Science Primer: Basic Concepts for Beginners; A Guide to Instagramming with Python for Data Analysis; New Poll: Python vs R vs rest; 4 Industries Being Transformed by Machine Learning and Robotics; A Guide to Understanding AI Toolkits

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Top Stories, Aug 7-13: Data Science Primer: Basic Concepts for Beginners; What Artificial Intelligence and Machine Learning Can Do – And What It Can’t - Aug 14, 2017.

Also: How I Used Deep Learning To Train A Chatbot To Talk Like Me; Making Predictive Models Robust: Holdout vs Cross-Validation; How Convolutional Neural Networks Accomplish Image Recognition?; Top Influencers for Data Science

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Top July Stories: The 4 Types of Data Analytics - Aug 8, 2017.

Also: 6 Reasons Why Python Is Suddenly Super Popular; When not to use deep learning; Machine Learning Applied to Big Data, Explained

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Top Stories, Jul 31-Aug 6: Machine Learning Algorithms: A Concise Technical Overview; Train your Deep Learning model faster and sharper: Snapshot Ensembling - Aug 7, 2017.

Also: Beautiful Python Visualizations: An Interview with Bokeh Core Developer; How will Big Data companies monetize data in 2018?; What is hardcore data science – in practice?; DeepSense: Time-series mobile sensing data processing; The Machine Learning Abstracts: Decision Trees

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Top Stories, Jul 24-30: When not to use Deep Learning; 6 Reasons Why Python Is Suddenly Super Popular - Jul 31, 2017.

Also: Machine Learning Exercises in Python: An Introductory Tutorial Series; Introduction to Neural Networks, Advantages and Applications; The Internet of Things: An Introductory Tutorial Series; The BI & Data Analysis Conundrum: 8 Reasons Why Many Big Data Analytics Solutions Fail to Deliver Value

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Top Stories, Jul 17-23: Machine Learning Applied to Big Data, Explained; 5 Free Resources for Getting Started with Deep Learning for Natural Language Processing - Jul 24, 2017.

Also: How GDPR Affects Data Science,AI and Deep Learning, Explained Simply; Are Most Machine Learning Experts Turning to Deep Learning?; Design by Evolution: How to evolve your neural network with AutoML

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Top Stories, Jul 10-16: The 4 Types of Data Analytics; What Are Artificial Intelligence, Machine Learning, and Deep Learning? - Jul 17, 2017.

Also: The Strange Loop in Deep Learning; How to Build a Data Science Pipeline; Automated Machine Learning - A Paradigm Shift That Accelerates Data Scientist Productivity; Medical Image Analysis with Deep Learning, Part 4

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Top June Stories: Top 15 Python Libraries for Data Science in 2017 - Jul 11, 2017.

Also 6 Interesting Things You Can Do with Python on Facebook Data; 7 Steps to Mastering Data Preparation with Python.

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Top Stories Jul 3-9: Applying Deep Learning to Real-world Problems; Advice to your younger Data Scientist Self? - Jul 10, 2017.

Also Top 15 Python Libraries for Data Science in 2017; Apache Flink: The Next Distributed Data Processing Revolution?

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Top Stories, Jun 26-Jul 2: Top 10 Quora Machine Learning Writers and Their Best Advice; Applying Deep Learning to Real-world Problems - Jul 3, 2017.

Top 10 Quora Machine Learning Writers and Their Best Advice, Updated, Applying Deep Learning to Real-world Problems; Using the TensorFlow API: An Introductory Tutorial Series; Text Clustering: Get quick insights from Unstructured Data; Why Artificial Intelligence and Machine Learning?

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Top Stories, Jun 19-25: Emerging Ecosystem: Data Science & Machine Learning Software, Analyzed; Machine Learning Algorithms in Self-Driving Cars - Jun 26, 2017.

Emerging Ecosystem: Data Science and Machine Learning Software, Analyzed; The Machine Learning Algorithms Used in Self-Driving Cars; The world’s first protein database for Machine Learning and AI; Making Sense of Machine Learning; 75 Big Data Terms to Know to Make your Dad Proud

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Top Stories, Jun 12-18: Top 15 Python Libraries for Data Science in 2017; Deep Learning Papers Reading Roadmap - Jun 19, 2017.

Top 15 Python Libraries for Data Science in 2017; Deep Learning Papers Reading Roadmap; The Practical Importance of Feature Selection; Understanding Deep Learning Requires Re-thinking Generalization; K-means Clustering with Tableau

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Top May Stories: KDnuggets Poll: Software for Analytics, Data Science, Machine Learning; How to Learn Machine Learning in 10 Days - Jun 13, 2017.

Also Machine Learning Workflows in Python from Scratch Part 1: Data Preparation; Deep Learning - Past, Present, and Future

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Top Stories, Jun 5-11: Is Regression Analysis Really Machine Learning?; 6 Interesting Things You Can Do with Python on Facebook Data - Jun 12, 2017.

Is Regression Analysis Really Machine Learning?; 6 Interesting Things You Can Do with Python on Facebook Data; A Practical Guide to Machine Learning; K-means Clustering with R: Call Detail Record Analysis; Machine Learning in Real Life: Tales from the Trenches to the Cloud

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Top Stories, May 29-Jun 4: Machine Learning Workflows in Python from Scratch; Machine Learning Algorithms Cheat Sheet - Jun 5, 2017.

Machine Learning Workflows in Python from Scratch Part 1: Data Preparation; Which Machine Learning Algorithm Should I Use?; 7 Steps to Mastering Data Preparation with Python; 7 Techniques to Handle Imbalanced Data; Why Does Deep Learning Not Have a Local Minimum?

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Top Stories, May 22-28: Analytics, Data Science, Machine Learning Software Poll Results; Machine Learning Crash Course - May 29, 2017.

New Leader, Trends, and Surprises in Analytics, Data Science, Machine Learning Software Poll; Machine Learning Crash Course: Part 1; Text Mining 101: Mining Information From A Resume; Data science platforms are on the rise and IBM is leading the way; An Introduction to the MXNet Python API

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Top Stories, May 15-21: Getting Into Data Science: What You Need to Know; The Best Python Packages for Data Science - May 22, 2017.

Getting Into Data Science: What You Need to Know; The Best Python Packages for Data Science; HDFS vs. HBase : All you need to know; What are common data quality issues for Big Data and how to handle them?; Teaching the Data Science Process

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Top Stories, May 8-14: Annual KDnuggets Data Science Software Poll; Using Deep Learning To Extract Knowledge From Job Descriptions - May 15, 2017.

New Poll: What software you used for Analytics, Data Mining, Data Science, Machine Learning projects in the past 12 months?; Using Deep Learning To Extract Knowledge From Job Descriptions; Deep Learning Past, Present, and Future; The Guerrilla Guide to Machine Learning with R

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Top Stories, May 1-7: How to Learn Machine Learning in 10 Days; Deep Learning – Past, Present, and Future - May 8, 2017.

How to Learn Machine Learning in 10 Days; Deep Learning – Past, Present, and Future; Keep it simple! How to understand Gradient Descent algorithm; New Poll: What software you used for Analytics, Data Mining, Data Science, Machine Learning projects in the past 12 months?

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Top April Stories: 10 Free Must-Read Books for Machine Learning and Data Science - May 6, 2017.

Also Forrester vs Gartner on Data Science Platforms; Top 20 Recent Research Papers on Machine Learning and Deep Learning.

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Top Stories, Apr 24-30: Guerrilla Guide to Machine Learning with Python; Understand the Gradient Descent Algorithm - May 1, 2017.

The Guerrilla Guide to Machine Learning with Python; How to understand Gradient Descent algorithm; Cartoon: Machine Learning – What They Think I Do; AI & Machine Learning Black Boxes: The Need for Transparency and Accountability; How to Build a Recurrent Neural Network in TensorFlow

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Top Stories, Apr 17-23: Awesome Deep Learning: Most Cited Deep Learning Papers; The Value of Exploratory Data Analysis - Apr 24, 2017.

Awesome Deep Learning: Most Cited Deep Learning Papers; The Value of Exploratory Data Analysis; 10 Free Must-Read Books for Machine Learning and Data Science; Forrester vs Gartner on Data Science Platforms and Machine Learning Solutions; Data Science for the Layman

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Top Stories, Apr 10-16: 10 Free Machine Learning & Data Science Books; 5 Machine Learning Projects You Can’t Overlook - Apr 17, 2017.

10 Free Must-Read Books for Machine Learning and Data Science; 5 Machine Learning Projects You Can No Longer Overlook, April; Forrester vs Gartner on Data Science Platforms and Machine Learning Solutions; Top mistakes data scientists make when dealing with business people

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Top Stories, Apr 3-9: Top 20 Machine Learning & Deep Learning Research Papers; Brief History of Artificial Intelligence - Apr 10, 2017.

Top 20 Recent Research Papers on Machine Learning and Deep Learning; A Brief History of Artificial Intelligence; Medical Image Analysis with Deep Learning; Introduction to Anomaly Detection; The 42 V’s of Big Data and Data Science

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Top March Stories: 7 More Steps to Mastering Machine Learning With Python; 50 Companies Leading The AI Revolution, Detailed - Apr 5, 2017.

Also Every Intro to Data Science Course on the Internet, Ranked; What Is Data Science, and What Does a Data Scientist Do?

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Top Stories, Mar 27-Apr 2: Standardization and Specialization in Data Science; What is Structural Equation Modeling? - Apr 3, 2017.

Standardization and Specialization in Analytics, Data Science, and BI; What is Structural Equation Modeling?; The Best R Packages for Machine Learning; What makes a great data scientist?; Deep Stubborn Networks - A Breakthrough Advance Towards Adversarial Machine Intelligence

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Top Stories, Mar 20-26: What Is Data Science, What Does a Data Scientist Do?; The Most Underutilized Function in SQL - Mar 27, 2017.

What Is Data Science, and What Does a Data Scientist Do?; The Most Underutilized Function in SQL; Getting Started with Deep Learning; Getting Up Close and Personal with Algorithms; How to think like a data scientist to become one

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Top Stories, Mar 13-19: 6 Business Concepts Data Science Unicorns Need; 50 Companies Leading The AI Revolution, Detailed - Mar 20, 2017.

Also 17 More Must-Know Data Science Interview Questions and Answers, Part 3; 7 Types of Data Scientist Job Profiles; Applying Machine Learning To March Madness

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Top Stories, Mar 6-12: What Makes a Good Data Science Visualization; A Ridiculously Specific Guide to Getting a Data Science Job - Mar 13, 2017.

What makes a good data visualization - a Data Scientist perspective; How to Get a Data Science Job: A Ridiculously Specific Guide; Visualizing Time-Series Change; Working With Numpy Matrices: A Handy First Reference; Beginner’s Guide to Customer Segmentation

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Top February Stories: 17 More Must-Know Data Science Interview Questions and Answers; 5 Career Paths in Big Data and Data Science, Explained - Mar 7, 2017.

Also Gartner 2017 Magic Quadrant for Data Science Platforms: gainers and losers; An Overview of Python Deep Learning Frameworks.

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Top Stories, Feb 27-Mar 5: 7 More Steps to Mastering Machine Learning With Python; An Overview of Python Deep Learning Frameworks - Mar 6, 2017.

7 More Steps to Mastering Machine Learning With Python; An Overview of Python Deep Learning Frameworks; Every Intro to Data Science Course on the Internet, Ranked; The Data Science Project Playbook; Hadoop Is Falling – Why?; Every Intro to Data Science Course on the Internet, Ranked

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Top Stories, Feb 20-26: The Anatomy of Deep Learning Frameworks; Gartner 2017 Magic Quadrant for Data Science Platforms - Feb 27, 2017.

The Anatomy of Deep Learning Frameworks; Gartner 2017 Magic Quadrant for Data Science Platforms; 17 More Must-Know Data Science Interview Questions and Answers; The Gentlest Introduction to Tensorflow - Part 3; The Origins of Big Data

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Top Stories, Feb 13-19: 17 More Must-Know Data Science Interview Questions and Answers • Removing Outliers Using Standard Deviation in Python - Feb 20, 2017.

17 More Must-Know Data Science Interview Questions and Answers • Removing Outliers Using Standard Deviation in Python • Natural Language Processing Key Terms, Explained • KDnuggets Top Blogger: An Interview with Brandon Rohrer

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Top Stories, Feb 6-12: 5 Career Paths in Big Data and Data Science, Explained • So What is Big Data? - Feb 13, 2017.

5 Career Paths in Big Data and Data Science, Explained • So What is Big Data? • Making Python Speak SQL with pandasql • 52 Useful Machine Learning & Prediction APIs, updated • Deep Learning Research Review: NLP

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Top January Stories: The Most Popular Language For Machine Learning and Data Science Is … - Feb 7, 2017.

Also 5 Machine Learning Projects You Can No Longer Overlook; Big Data and the Internet of Things don't make business smarter, Analytics and Data Science do.

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Top Stories, Jan 30-Feb 5: Deep Learning Research Review: Natural Language Processing; Data Scientist – best job in America, again - Feb 6, 2017.

Deep Learning Research Review: Natural Language Processing; Data Scientist – best job in America, again; 5 Free Courses for Getting Started in Artificial Intelligence; Top R Packages for Machine Learning

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Top Stories, Jan 23-29: 6 Areas of AI and Machine Learning to Watch Closely; Pandas Cheat Sheet: Data Science and Data Wrangling in Python - Jan 30, 2017.

6 Areas of AI and Machine Learning to Watch Closely; Pandas Cheat Sheet; Great Collection of Minimal and Clean Implementations of Machine Learning Algorithms; Chatbots on Steroids: 10 Key Machine Learning Capabilities to Fuel Your Chatbot; The Top Predictive Analytics Pitfalls to Avoid

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Top Stories, Jan 16-22: Time Series Analysis: A Primer; Deep Learning Can be Applied to Natural Language Processing - Jan 23, 2017.

Time Series Analysis: A Primer; Deep Learning Can be Applied to Natural Language Processing; The Current State of Automated Machine Learning; Introduction to Forecasting with ARIMA in R; 90 Active Blogs on Analytics, Big Data, Data Mining, Data Science, Machine Learning

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Top Stories, Jan 9-15: The Most Popular Language For Machine Learning and Data Science; Analytics and Data Science Make Business Smarter - Jan 16, 2017.

The Most Popular Language For Machine Learning and Data Science; Analytics and Data Science Make Business Smarter; Exclusive Interview with Jeremy Howard; 5 Machine Learning Projects You Can No Longer Overlook, January

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Top Stories, Jan 2-8: 5 Machine Learning Projects You Can No Longer Overlook, January; Machine Learning and Cyber Security Resources - Jan 9, 2017.

5 Machine Learning Projects You Can No Longer Overlook, January; Machine Learning and Cyber Security Resources; Generative Adversarial Networks - Hot Topic in Machine Learning; Ten Myths About Machine Learning

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Top December Stories: 50+ Data Science, Machine Learning Cheat Sheets; Machine Learning/AI: Main 2016 Developments, Key 2017 Trends - Jan 5, 2017.

Also Why Deep Learning is Radically Different From Machine Learning; Bayesian Basics, Explained

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Top Stories, Dec 26-Jan 1: Game Theory Reveals the Future of Deep Learning; A Funny Look at Big Data and Data Science - Jan 2, 2017.

Game Theory Reveals the Future of Deep Learning; A Funny Look at Big Data and Data Science; Machine Learning & Artificial Intelligence: Main Developments in 2016 and Key Trends in 2017; How I Detect Fake News, by Tim O’Reilly

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Top Stories, Dec 19-25: Machine Learning & AI: Main Developments in 2016 and Key Trends in 2017; 4 Reasons Your Machine Learning Model is Wrong - Dec 27, 2016.

Machine Learning & AI: Main Developments in 2016 and Key Trends in 2017; 4 Reasons Your Machine Learning Model is Wrong (and How to Fix It); 50+ Data Science, Machine Learning Cheat Sheets; First Deep Learning for coders MOOC

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Top Stories, Dec 12-18: Data Science, Predictive Analytics 2016 Developments, 2017 Key Trends; 50+ Data Science, Machine Learning Cheat Sheets - Dec 19, 2016.

50+ Data Science, Machine Learning Cheat Sheets, updated; Data Science, Predictive Analytics Main Developments in 2016 and Key Trends for 2017; Bayesian Basics, Explained; Data Analytics Models in Quantitative Finance and Risk Management

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Top 2016 KDnuggets Stories: Must-Know Data Science Interview Q&A, 10 Algorithms Machine Learning Engineers Need to Know - Dec 15, 2016.

Also 20 Questions to Detect Fake Data Scientists; Software used for Analytics, Data Science, Machine Learning projects; Top Algorithms and Methods Used by Data Scientists

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Top Stories, Dec 5-11: Why Deep Learning is Radically Different From Machine Learning; Data Science Trends To Look Out For In 2017 - Dec 12, 2016.

Why Deep Learning is Radically Different From Machine Learning; Data Science Trends To Look Out For In 2017; Bayesian Basics, Explained; Big Data: Main Developments in 2016 and Key Trends in 2017; 4 Cognitive Bias Key Points Data Scientists Need to Know

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Top November Stories: Trump, Failure of Prediction, and Lessons for Data Scientists - Dec 6, 2016.

Also: How Bayesian Inference Works; Top 20 Python Machine Learning Open Source Projects, updated; Machine Learning vs Statistics

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Top Stories, Nov 28-Dec 4: Machine Learning vs Statistics; Hard Thing About Deep Learning; Developers’ Machine Learning Intro - Dec 5, 2016.

Machine Learning vs Statistics; The hard thing about deep learning; Top 20 Python Machine Learning Open Source Projects, updated; Tips for Beginner Machine Learning/Data Scientists Feeling Overwhelmed; Introduction to Machine Learning for Developers

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Top Stories, Nov 21-27: Top 20 Python Machine Learning Open Source Projects; Continuous Improvement for IoT - Nov 28, 2016.

Top 20 Python Machine Learning Open Source Projects, updated; Continuous improvement for IoT through AI; Top 10 Facebook Groups for Big Data, Data Science, and Machine Learning; Linear Regression, Least Squares & Matrix Multiplication: A Concise Technical Overview

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Top Stories, Nov 14-20: How Bayesian Inference Works; Data Science and Big Data, Explained; Advanced Time Series Prediction - Nov 21, 2016.

How Bayesian Inference Works; Data Science and Big Data, Explained; Trump, Failure of Prediction, and Lessons for Data Scientist; Combining Different Methods to Create Advanced Time Series Prediction; Questions To Ask When Moving Machine Learning From Practice to Production

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Top Stories, Nov 7-13: Trump, Failure of Prediction, and Lessons for Data Scientists; Top 10 Amazon Books in Data Mining - Nov 14, 2016.

Trump, Failure of Prediction, and Lessons for Data Scientists; Top 10 Amazon Books in Data Mining; Data Science Basics: An Introduction to Ensemble Learners; Parallelism in Machine Learning: GPUs, CUDA, and Practical Applications; 5 Free Machine Learning EBooks

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Top Stories, Oct 31-Nov 6: Machine Learning: A Complete and Detailed Overview; Learn Data Science for Excellence - Nov 7, 2016.

Machine Learning: A Complete and Detailed Overview; Learn Data Science for Excellence; 5 EBooks to Read Before Getting into A Machine Learning Career; Eight Things an R user Will Find Frustrating When Trying to Learn Python

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Top October Stories: 5 EBooks to Read Before Getting into A Machine Learning Career; Top 10 Data Science Videos on Youtube - Nov 6, 2016.

Also Battle of the Data Science Venn Diagrams; Deep Learning Key Terms, Explained.

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Top Stories, Oct 24-30: 5 EBooks to Read Before Getting into Machine Learning; Big Data Science: Expectation vs. Reality - Oct 31, 2016.

5 EBooks to Read Before Getting into A Machine Learning Career; Big Data Science: Expectation vs. Reality; Mind of a Data Scientist; Machine Learning: A Complete and Detailed Overview; Using Machine Learning to Detect Malicious URLs

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Top Stories, Oct 17-23: Top 10 Data Science Videos on YouTube; 5 EBooks to Read Before Getting into A Machine Learning Career - Oct 24, 2016.

Top 10 Data Science Videos on YouTube; 5 EBooks to Read Before Getting into A Machine Learning Career; Jupyter Notebook Best Practices for Data Science; A Beginners Guide to Neural Networks with Python and SciKit Learn 0.18!; European Machine Intelligence Landscape

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Top Stories, Oct 10-16: Deep Learning Key Terms, Explained; Artificial Intelligence, Deep Learning, and Neural Networks, Explained - Oct 17, 2016.

Deep Learning Key Terms, Explained; Artificial Intelligence, Deep Learning, and Neural Networks, Explained; Top 12 Interesting Careers to Explore in Big Data; Data Preparation Tips, Tricks, and Tools: An Interview with the Insiders; Here's How IT Departments are Using Big Data

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Top 10 KDnuggets Blog Posts, looking back a year - Oct 11, 2016.

Have a look at our top blog posts of Q4 2015, some of which continue to be among the most popular on our site, while others are still topical and warrant a second look.

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Top Stories, Oct 3-9: Battle of the Data Science Venn Diagrams; Automated Data Science & Machine Learning: An Interview with the Auto-sklearn Team - Oct 10, 2016.

Battle of the Data Science Venn Diagrams; Automated Data Science & Machine Learning: An Interview with the Auto-sklearn Team; The 10 Algorithms Machine Learning Engineers Need to Know; Top Algorithms and Methods Used by Data Scientists; Biggest Issues in Data Science

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Top September Stories: Top Algorithms and Methods Used by Data Scientists - Oct 8, 2016.

Also A Beginner's Guide To Understanding Convolutional Neural Networks; Data Science for IoT: 10 Differences; 9 Key Deep Learning Papers, Explained.

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Top Stories, Sep 26-Oct 2: Data Science for Internet of Things (IoT); Claudia Perlich on Biggest Issues in Data Science - Oct 3, 2016.

Data Science for Internet of Things (IoT) : Ten Differences From Traditional Data Science; Claudia Perlich on Biggest Issues in Data Science; Data Science Basics: Data Mining vs. Statistics; The 10 Algorithms Machine Learning Engineers Need to Know; Top Algorithms and Methods Used by Data Scientists

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Top Stories, Sep 18-24: Top Algorithms and Methods Used by Data Scientists; 9 Key Deep Learning Papers, Explained - Sep 25, 2016.

Also - the 10 Algorithms Machine Learning Engineers Need to Know; Learning From Data (Intro Machine Learning) Caltech course starts on edX.

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Top Stories, Sep 12-18: Top Algorithms Used by Data Scientists; 7 Steps to Mastering Apache Spark 2.0 - Sep 19, 2016.

Top Algorithms Used by Data Scientists; 7 Steps to Mastering Apache Spark 2.0; The (Not So) New Data Scientist Venn Diagram; Behind the Dream of Data Work as it Could Be; The Deception of Supervised Learning

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Top Stories, Sep 5-11: Beginners Guide To Convolutional Neural Networks; Big Data Dilemma: Save Money or Make Money - Sep 12, 2016.

Beginners Guide To Convolutional Neural Networks; Big Data Dilemma: Save Me Money Versus Make Me Money; The 10 Algorithms Machine Learning Engineers Need to Know; How to Become a Data Scientist

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Top August Stories: The 10 Algorithms Machine Learning Engineers Need to Know; How to Become a Data Scientist - Sep 6, 2016.

Also - A Beginner Guide to Neural Networks with R; Data Science for Beginners: Fantastic Introductory Video Series from Microsoft.

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Top Stories, Aug 29-Sep 4: How Convolutional Neural Networks Work; Activation Functions in Neural Networks - Sep 5, 2016.

How Convolutional Neural Networks Work; Activation Functions in Neural Networks; The 10 Algorithms Machine Learning Engineers Need to Know; How to Become a Data Scientist; Learning from Imbalanced Classes

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Top Stories, Aug 22-28: How to Become a Data Scientist; 10 Need to Know Machine Learning Algorithms - Aug 29, 2016.

How to Become a Data Scientist; 10 Need to Know Machine Learning Algorithms; How to Become a (Type A) Data Scientist; Cartoon: Data Scientist: The sexiest job of the 21st century until...

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Top Stories, Aug 15-21: 10 Need to Know Machine Learning Algorithms; Does Data Scientist Mean What You Think It Means? - Aug 22, 2016.

The 10 Algorithms Machine Learning Engineers Need to Know; Does Data Scientist Mean What You Think It Means?; The Gentlest Introduction to Tensorflow; Central Limit Theorem for Data Science - Part 2

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Top Stories, Aug 8-14: Beginner’s Guide to Neural Nets with R; 5 Data Science/Big Data Ebooks - Aug 15, 2016.

Beginner's Guide to Neural Networks with R; 5 EBooks to Read Before Getting into A Data Science or Big Data Career; Cartoon: Make Data Great Again; Understanding the Bias-Variance Tradeoff: An Overview

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Top Stories, Aug 1-7: Bayesian Machine Learning, Explained; Data Science for Beginners Video Series - Aug 8, 2016.

Bayesian Machine Learning, Explained; Data Science for Beginners Video Series; What Statistics Topics are Needed for Excelling at Data Science?; The Core of Data Science

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Top July stories: Bayesian Machine Learning, Explained; Why Big Data is in Trouble: They Forgot About Applied Statistics - Aug 6, 2016.

Also - How to Start Learning Deep Learning; What Has Pokemon Got To Do With Big Data?

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Top Stories, July 25-31: What Has Pokemon Got To Do With Big Data?; 35 Open Source tools for Internet of Things - Aug 1, 2016.

What Has Pokemon Got To Do With Big Data?; 35 Open Source tools for Internet of Things; 7 Steps to Understanding NoSQL Databases; SAS vs R vs Python: Which Tool Do Analytics Pros Prefer?

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Top Stories, July 18-24: Why Big Data is in Trouble; In Deep Learning, Architecture Engineering is the New Feature Engineering - Jul 25, 2016.

Why Big Data is in Trouble: They Forgot About Applied Statistics; In Deep Learning, Architecture Engineering is the New Feature Engineering; 5 Big Data Projects You Can No Longer Overlook; What Has Pokemon Got To Do With Big Data?

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Top Stories, July 11–17: Top Machine Learning MOOCs and Online Lectures; Bayesian Machine Learning, Explained - Jul 18, 2016.

Top Machine Learning MOOCs and Online Lectures; Bayesian Machine Learning, Explained; 10 Algorithm Categories for A.I., Big Data, and Data Science; 5 Deep Learning Projects You Can No Longer Overlook; The Hard Problems AI Can't (Yet) Touch

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Top Stories, July 4–10: The Invention of Support Vector Machines; Storytelling: The Power to Influence in Data Science - Jul 11, 2016.

Data Mining History: The Invention of Support Vector Machines; Storytelling: The Power to Influence in Data Science; Support Vector Machines: A Simple Explanation; Big Data, Bible Codes, and Bonferroni

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Top June stories: The Difference Deep Learning and “Regular” Machine Learning? R, Python duel as top Data Science tools. - Jul 5, 2016.

Also Data Science of Variable Selection; The Big Data Ecosystem is Too Damn Big.

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Top Stories, June 27 – July 3: Big Data Ecosystem is Too Damn Big; 5 More Machine Learning Projects You Can’t Overlook - Jul 4, 2016.

The Big Data Ecosystem is Too Damn Big; 5 More Machine Learning Projects You Can No Longer Overlook; 7 Steps to Mastering Machine Learning With Python; Machine Learning Trends and the Future of Artificial Intelligence

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Top Stories, June 20-26: New Machine Learning Book, Free Draft Chapters; Machine Learning Trends & Future of A.I. - Jun 27, 2016.

New Andrew Ng Machine Learning Book Under Construction, Free Draft Chapters; Machine Learning Trends and the Future of Artificial Intelligence; Top Machine Learning Libraries for Javascript; 7 Steps to Mastering Machine Learning With Python

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Top Stories, June 13-19: A Visual Explanation of the Back Propagation Algorithm; Apache Spark Key Terms, Explained - Jun 20, 2016.

A Visual Explanation of the Back Propagation Algorithm for Neural Networks; Apache Spark Key Terms, Explained; What Big Data, Data Science, Deep Learning software goes together?; 10 Data Acquisition Strategies for Startups; 7 Steps to Mastering Machine Learning With Python

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Top Stories, June 6-12: Data Science of Variable Selection; R, Python Duel As Top Analytics, Data Science Software - Jun 13, 2016.

Data Science of Variable Selection; R, Python Duel As Top Analytics, Data Science Software; Big Data Business Model Maturity Index and the Internet of Things (IoT); Where are the Opportunities for Machine Learning Startups?

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Top Stories, May 30 – June 6: Difference Between Deep Learning and “Regular” Machine Learning; Introduction to Numpy - Jun 6, 2016.

Difference Between Deep Learning and “Regular” Machine Learning; An Introduction to Scientific Python (and a Bit of the Maths Behind It) – NumPy; How to Build Your Own Deep Learning Box; Interacting with Machine Learning - Here is Why You Should Care

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Top Stories, May 23-29: Machine Learning Key Terms, Explained; 10 Must Have Data Science Skills, Updated - May 30, 2016.

Machine Learning Key Terms, Explained; 10 Must Have Data Science Skills, Updated; A Concise Overview of Standard Model-fitting Methods; Free eBook: Healthcare Social Media Analytics and Marketing; 7 Steps to Mastering Machine Learning With Python

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Top stories, May 16-22: Annual KDnuggets Analytics Software Poll; How to Explain Machine Learning to Software Engineers - May 23, 2016.

Annual KDnuggets Analytics Software Poll; How to Explain Machine Learning to a Software Engineer; 5 Machine Learning Projects You Can No Longer Overlook; Doing Data Science: A Kaggle Walkthrough Part 1 – Introduction

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Top stories for May 9-15: Data scientists mostly just do arithmetic, Data Scientists – future-proof yourselves - May 16, 2016.

Data scientists mostly just do arithmetic and that’s a good thing; Data Scientists – future-proof yourselves; Are Deep Neural Networks Creative?; Implementing Neural Networks in Javascript; 7 Steps to Mastering Machine Learning With Python

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Top stories for May 1-7: Why Implement Machine Learning Algorithms From Scratch? 7 Steps to Mastering Machine Learning With Python - May 8, 2016.

How to Use Cohort Analysis to Improve Customer Retention; Why Implement Machine Learning Algorithms From Scratch?; 7 Steps to Mastering Machine Learning With Python; R vs Python for Data Science: The Winner is ...

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Top April stories: 10 Essential Books for Data Enthusiast; When Deep Learning is better than SVMs or Random Forests? - May 5, 2016.

Top 10 Essential Books for the Data Enthusiast; 10 Signs Of A Bad Data Scientist; When Does Deep Learning Work Better Than SVMs or Random Forests?; Comprehensive Guide to Learning Python for Data Science and more.

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Top stories, Apr 24-30: How to Remove Duplicates in Large Datasets; The “Thinking” Part of “Thinking Like A Data Scientist” - May 1, 2016.

7 Steps to Mastering Machine Learning With Python; When Does Deep Learning Work Better Than SVMs or Random Forests; How to Remove Duplicates in Large Datasets; The "Thinking" Part of "Thinking Like A Data Scientist".

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Top stories for Apr 18-24: Top 15 Machine Learning Frameworks, Deep Learning vs. SVMs and Random Forests - Apr 25, 2016.

When Does Deep Learning Work Better Than SVMs or Random Forests?; Comprehensive Guide to Learning Python for Data Analysis and Data Science; Top 15 Frameworks for Machine Learning Experts; Top 10 IPython Notebook Tutorials for Data Science and Machine Learning

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Top stories for Apr 10-17: New Deep Learning Book Finished, Pocket Guide to Data Science - Apr 18, 2016.

New Deep Learning Book Finished; A Pocket Guide to Data Science; 7 Steps to Mastering Machine Learning With Python; From Science to Data Science, a Comprehensive Guide for Transition; Automated Machine Learning: Changing the Game

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Top stories for Apr 3-9: Deep Learning for Internet of Things Using H2O; Basics of GPU Computing for Data Scientists - Apr 10, 2016.

7 Steps to Mastering Machine Learning With Python; Top 10 Essential Books for the Data Enthusiast; Deep Learning for Internet of Things Using H2O; Basics of GPU Computing for Data Scientists.

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Top March stories: R Learning Path: From beginner to expert in 7 steps; R or Python? Consider learning both - Apr 5, 2016.

R Learning Path: From beginner to expert in 7 steps; R or Python? Consider learning both; Distributed TensorFlow Has Arrived; The Data Science Process, Rediscovered.

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Top stories for Mar 27- Apr 2: 100 Active Blogs on Big Data, Data Science; Become A Machine Learning Expert in one step - Apr 3, 2016.

100 Active Blogs on Analytics, Big Data, Data Mining, Data Science, Machine Learning; How To Become A Machine Learning Expert In One Simple Step; R Learning Path: From beginner to expert in R in 7 steps; 7 Steps to Mastering Machine Learning With Python.

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Top stories for Mar 20-26: R Learning Path: From beginner to expert in 7 steps; Top 10 Data Science Resources on Github - Mar 27, 2016.

R Learning Path: From beginner to expert in R in 7 steps; Top 10 Data Science Resources on Github; 7 Steps to Mastering Machine Learning With Python; 21 Must-Know Data Science Interview Questions and Answers.

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Top stories for Mar 13-19: After 150 Years, the ASA Says No to p-values; New KDnuggets Tutorials Page - Mar 20, 2016.

After 150 Years, the ASA Says No to p-values; New KDnuggets Tutorials Page: Learn R, Python, Data Visualization, Data Science, and more. R vs Python for Data Science: The Winner is ...

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Top stories for Mar 6-12: R or Python? Consider learning both; The Data Science Process, Rediscovered - Mar 13, 2016.

R or Python? Consider learning both; The Data Science Process, Rediscovered; R vs Python for Data Science: The Winner is ...; 7 Steps to Mastering Machine Learning With Python.

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Top February stories: 21 Must-Know Data Science Interview Q&A; Gartner 2016 MQ for Advanced Analytics: gainers and losers - Mar 8, 2016.

21 Must-Know Data Science Interview Questions and Answers; Top 10 TED Talks for the Data Scientists; Gartner 2016 Magic Quadrant for Advanced Analytics Platforms: gainers and losers.

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Top stories for Feb 28 – Mar 5: The Data Science Process; Why Spark Reached the Tipping Point in 2015 - Mar 6, 2016.

R vs Python for Data Science: The Winner is ...; 7 Steps to Mastering Machine Learning With Python; The Data Science Process; Why Spark Reached the Tipping Point in 2015.

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Top stories for Feb 21-27: 21 Must-Know Data Science Interview Q&A, part 2; Data Science vs Disease - Feb 28, 2016.

21 Must-Know Data Science Interview Questions and Answers, parts 1 and 2; Top 10 TED Talks for the Data Scientists; How Data Science is Fighting Disease; Top Data Visualization Projects on Github.

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Top stories for Feb 14-20: Gartner 2016 MQ for Advanced Analytics: gainers and losers; 21 Must-Know Data Science Interview Q&A - Feb 21, 2016.

21 Must-Know Data Science Interview Questions and Answers; Gartner 2016 Magic Quadrant for Advanced Analytics Platforms; The Next Big Inflection in Big Data: Automated Insights; Opening Up Deep Learning For Everyone.

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Top stories for Feb 7-13: Top 10 TED Talks for the Data Scientists; Easy Deep Learning with TensorFlow and Scikit-learn - Feb 14, 2016.

50+ Data Science and Machine Learning Cheat Sheets; 20 Questions to Detect Fake Data Scientists; Top 10 TED Talks for the Data Scientists; Scikit Flow: Easy Deep Learning with TensorFlow and Scikit-learn.

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Top stories for Jan 31 – Feb 6: Data scientists keep forgetting the one rule; Apache Spark: RDD, DataFrame or Dataset? - Feb 7, 2016.

20 Q to Detect Fake Data Scientists; TensorFlow Disappoints - Google Deep Learning falls shallow; Data scientists keep forgetting the one rule; Apache Spark: RDD, DataFrame or Dataset?

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Top January stories: 20 Questions to Detect Fake Data Scientists, Machine Intelligence vs. Machine Learning vs. Deep Learning vs. AI - Feb 5, 2016.

20 Questions to Detect Fake Data Scientists; What Is Machine Intelligence Vs. Machine Learning Vs. Deep Learning Vs. Artificial Intelligence (AI)? 7 Common Data Science Mistakes and How to Avoid Them; What questions can data science answer?

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Top stories for Jan 24-30: 7 Common Data Science Mistakes; Businesses Will Need 1M Data Scientists by 2018 - Jan 31, 2016.

20 Questions to Detect Fake Data Scientists; TensorFlow Disappoints - Google Deep Learning falls shallow; 7 Common Data Science Mistakes and How to Avoid Them; Businesses Will Need One Million Data Scientists by 2018.

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Top stories for Jan 17-23: 20 Questions to Detect Fake DS; Yahoo Releases the Largest-ever Machine Learning Dataset - Jan 24, 2016.

20 Questions to Detect Fake Data Scientists; Google Deep Learning TensorFlow Disappoints; Yahoo Releases the Largest-ever Machine Learning Dataset for Researchers; Research Leaders on Data Mining, Data Science and Big Data.

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Top 2015 KDnuggets Stories on Analytics, Big Data, Data Science, Data Mining, Machine Learning, updated - Jan 21, 2016.

R vs Python for Data Science: The Winner is ...; 60+ Free Books on Big Data, Data Science, Data Mining, Machine Learning; Top 20 Python Machine Learning Open Source Projects; 50+ Data Science and Machine Learning Cheat Sheets.

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