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• Basic Image Data Analysis Using Python – Part 3 - Sep 28, 2018.
  
  Accessing the internal component of digital images using Python packages becomes more convenient to help understand its properties, as well as nature.

  Computer Vision, Image Processing, numpy, Python

• Introduction to Deep Learning - Sep 28, 2018.
  
  I decided to begin to put some structure in my understanding of Neural Networks through this series of articles.

  Beginners, Deep Learning, Neural Networks

• Visualising Geospatial data with Python using Folium - Sep 27, 2018.
  
  Folium is a powerful data visualization library in Python that was built primarily to help people visualize geospatial data. With Folium, one can create a map of any location in the world if its latitude and longitude values are known. This guide will help you get started.

  Data Visualization, Geospatial, GitHub, Python

• Raspberry Pi IoT Projects for Fun and Profit - Sep 27, 2018.
  
  In this post, I will explain how to run an IoT project from the command line, without graphical interface, using Ubuntu Core in a Raspberry Pi 3.

  Pages: 1 2

  Data Science, IoT, Python, Raspberry Pi

• Introducing Path Analysis Using R - Sep 27, 2018.
  
  Path analysis is an extension of multiple regression. It allows for the analysis of more complicated models.

  Analysis, Analytics, R

• Principles of Database Management: The Practical Guide to Storing, Managing and Analyzing Big and Small Data - Sep 26, 2018.
  
  This comprehensive textbook teaches the fundamentals of database design, modeling, systems, data storage, and the evolving world of data warehousing, governance and more.

  Bart Baesens, Book, Database Management

• Power Laws in Deep Learning 2: Universality - Sep 26, 2018.
  
  It is amazing that Deep Neural Networks display this Universality in their weight matrices, and this suggests some deeper reason for Why Deep Learning Works.

  Deep Learning, Explained, Neural Networks

• Introducing VisualData: A Search Engine for Computer Vision Datasets - Sep 26, 2018.
  
  Instead of building your own dataset, there already exists a rich collection of computer vision datasets contributed by academic researchers, hobbyists and companies.

  Computer Vision, Datasets

• Unfolding Naive Bayes From Scratch - Sep 25, 2018.
  
  Whether you are a beginner in Machine Learning or you have been trying hard to understand the Super Natural Machine Learning Algorithms and you still feel that the dots do not connect somehow, this post is definitely for you!

  Pages: 1 2

  Bayesian, Classification, Naive Bayes, Probability, Statistics

• When Bayes, Ockham, and Shannon come together to define machine learning - Sep 25, 2018.
  
  A beautiful idea, which binds together concepts from statistics, information theory, and philosophy.

  Bayes Theorem, Machine Learning

• Building a Machine Learning Model through Trial and Error - Sep 24, 2018.
  
  A step-by-step guide that includes suggestions on how to preprocess data and deriving features from this. This article also contains links to help you explore additional resources about machine learning methods and other examples.

  Deployment, Machine Learning, MathWorks

• Diversity in Data Science: Overview and Strategy - Sep 24, 2018.
  
  We take a hard look at diversity within the tech industry, root causes, and potential solutions and highlight resources/initiatives that can connect readers with programs aiding their professional development.

  Career, Data Science, Diversity, Hiring, Trends, Women

• Deep Learning Framework Power Scores 2018 - Sep 24, 2018.
  
  Who’s on top in usage, interest, and popularity?

  CNTK, Deep Learning, fast.ai, Java, Keras, MXNet, Python, PyTorch, TensorFlow, Theano

• Cartoon: Where AI achieves excellence - Sep 22, 2018.
  
  We examine what can happen when lawyers are replaced with Machine Learning.

  AI, Cartoon, Humans vs Machines, Law

• Data Capture – the Deep Learning Way - Sep 21, 2018.
  
  An overview of how an information extraction pipeline built from scratch on top of deep learning inspired by computer vision can shakeup the established field of OCR and data capture.

  Deep Learning, Image Recognition

• Machine Learning: How to Build a Model From Scratch - Sep 20, 2018.
  
  Register now for upcoming webinar, Building a Machine Learning Fraud Model with Momentum Travel, on Sep 27 @ 10 AM PT.

  Machine Learning, Modeling, WhitePages

• 6 Steps To Write Any Machine Learning Algorithm From Scratch: Perceptron Case Study - Sep 20, 2018.
  
  Writing a machine learning algorithm from scratch is an extremely rewarding learning experience. We highlight 6 steps in this process.

  Data Science, Machine Learning, Neural Networks

• Power Laws in Deep Learning - Sep 20, 2018.
  
  In pretrained, production quality DNNs,  the weight matrices for the Fully Connected (FC ) layers display Fat Tailed Power Law behavior.

  Deep Learning, Explained, Neural Networks

• Deep Learning on the Edge - Sep 19, 2018.
  
  Detailed analysis into utilizing deep learning on the edge, covering both advantages and disadvantages and comparing this against more traditional cloud computing methods.

  Cloud Computing, Deep Learning, IoT, Security

• Data Augmentation For Bounding Boxes: Rethinking image transforms for object detection - Sep 19, 2018.
  
  Data Augmentation is one way to battle this shortage of data, by artificially augmenting our dataset. In fact, the technique has proven to be so successful that it's become a staple of deep learning systems.

  Pages: 1 2

  Deep Learning, Image Recognition, Neural Networks, Object Detection, Python

• SQL Case Study: Helping a Startup CEO Manage His Data - Sep 19, 2018.
  
  In this tutorial, you will learn how to create a table, insert values into it, use and understand some data types, use SELECT statements, UPDATE records, use some aggregate functions, and more.

  Pages: 1 2

  SQL, Startup

• How many data scientists are there and is there a shortage? - Sep 18, 2018.
  
  We examine the famous McKinsey prediction from 2011 and look into whether there a shortage of people with analytical expertise and estimate how many Data Scientists are there.

  Data Scientist, Glassdoor, indeed, Jobs, Kaggle, LinkedIn, McKinsey

• Free resources to learn Natural Language Processing - Sep 18, 2018.
  
  An extensive list of free resources to help you learn Natural Language Processing, including explanations on Text Classification, Sequence Labeling, Machine Translation and more.

  Beginners, Machine Learning, Machine Translation, NLP, Sentiment Analysis, Text Classification

• A Winning Game Plan For Building Your Data Science Team - Sep 18, 2018.
  
  We need to understand the responsibilities, capabilities, expectations and competencies of the Data Engineer, Data Scientist and Business Stakeholder.

  Data Engineering, Data Science, Data Science Team

• You Aren’t So Smart: Cognitive Biases are Making Sure of It - Sep 17, 2018.
  
  Cognitive biases are tendencies to think in certain ways that can lead to systematic deviations from a standard of rationality or good judgment. They have all sorts of practical impacts on our lives, whether we want to admit it or not.

  Bias, Cognitive Bias, Confirmation Bias

• Ethics + Data Science: opinion by DJ Patil, former US Chief Data Scientist - Sep 14, 2018.
  
  How much has data changed our lives over the past decade? Former US Chief Data Scientist DJ Patil investigates.

  Data Science, DJ Patil, Ethics, Social Good

• The Growing Participation of Women in the Data Science Community - Sep 14, 2018.
  
  We still have a long way to go before the gender representation becomes more equalized, but the field at large indicates hopeful trends about women working in the role or desiring to do so in the future.

  Data Science, STEM, Women

• The Economics and Benefits of Artificial Intelligence - Sep 13, 2018.
  
  In this article, focus on current AI, which is mostly based on the algorithms that can do predictions, and discuss how the economics of AI works and how it may affect business.

  AI, Economics, Humans

• Hadoop for Beginners - Sep 12, 2018.
  
  An introduction to Hadoop, a framework that enables you to store and process large data sets in parallel and distributed fashion.

  Beginners, Big Data, Hadoop

• Iterative Initial Centroid Search via Sampling for k-Means Clustering - Sep 12, 2018.
  
  Thinking about ways to find a better set of initial centroid positions is a valid approach to optimizing the k-means clustering process. This post outlines just such an approach.

  Clustering, K-means, Python, Sampling, scikit-learn

• Machine Learning Cheat Sheets - Sep 11, 2018.
  
  Check out this collection of machine learning concept cheat sheets based on Stanord CS 229 material, including supervised and unsupervised learning, neural networks, tips & tricks, probability & stats, and algebra & calculus.

  Cheat Sheet, Deep Learning, Machine Learning, Mathematics, Neural Networks, Probability, Statistics, Supervised Learning, Tips, Unsupervised Learning

• Machine Learning for Text Classification Using SpaCy in Python - Sep 11, 2018.
  
  In this post, we will demonstrate how text classification can be implemented using spaCy without having any deep learning experience.

  NLP, Python, Text Analytics, Text Classification, Text Mining

• What is Web Scraping and Why You Should Learn It? - Sep 10, 2018.
  
  Introducing Octoparse - a sleek, powerful and easy-to-use software that makes web scraping from any websites achievable for most people, including non-coders.

  Glassdoor, Industry, LinkedIn, Octoparse, Web Scraping

• Object Detection and Image Classification with YOLO - Sep 10, 2018.
  
  We explain object detection, how YOLO algorithm can help with image classification, and introduce the open source neural network framework Darknet.

  Image Recognition, Object Detection, YOLO

• Webinar: Life as a Data Scientist, Sep 12 - Sep 8, 2018.
  
  Watch Springboard webinar and learn everything from the hard skills to the soft skills aspiring data scientists need. Springboard Data Science Career Track now offers deferred tuition - learn more.

  Career, Data Science Education, Data Science Skills, Springboard

• Neural Networks and Deep Learning: A Textbook - Sep 7, 2018.
  
  This book covers both classical and modern models in deep learning. The book is intended to be a textbook for universities, and it covers the theoretical and algorithmic aspects of deep learning.

  Book, Charu Aggarwal, Deep Learning, Neural Networks

• Journey to Machine Learning – 100 Days of ML Code - Sep 7, 2018.
  
  A personal account from Machine Learning enthusiast Avik Jain on his experiences of #100DaysOfMLCode, a challenge that encourages beginners to code and study machine learning for at least an hour, every day for 100 days.

  GitHub, K-nearest neighbors, Machine Learning, Python, SVM

• 5 Things to Know About A/B Testing - Sep 7, 2018.
  
  This article presents 5 things to know about A/B testing, from appropriate sample sizes, to statistical confidence, to A/B testing usefulness, and more.

  A/B Testing, Applied Statistics, Psychology, Statistics

• Ultimate Guide to Getting Started with TensorFlow - Sep 6, 2018.
  
  Including video and written tutorials, beginner code examples, useful tricks, helpful communities, books, jobs and more - this is the ultimate guide to getting started with TensorFlow.

  Deep Learning, Dropout, Python, TensorFlow

• Data Science Cheat Sheet - Sep 6, 2018.
  
  Check out this new data science cheat sheet, a relatively broad undertaking at a novice depth of understanding, which concisely packs a wide array of diverse data science goodness into a 9 page treatment.

  Cheat Sheet, Data Science

• Don’t Use Dropout in Convolutional Networks - Sep 5, 2018.
  
  If you are wondering how to implement dropout, here is your answer - including an explanation on when to use dropout, an implementation example with Keras, batch normalization, and more.

  Convolutional Neural Networks, Dropout, Keras

• Deep Learning for NLP: An Overview of Recent Trends - Sep 5, 2018.
  
  A new paper discusses some of the recent trends in deep learning based natural language processing (NLP) systems and applications. The focus is on the review and comparison of models and methods that have achieved state-of-the-art (SOTA) results on various NLP tasks and some of the current best practices for applying deep learning in NLP.

  Pages: 1 2

  Deep Learning, NLP, Word Embeddings, word2vec

• What on earth is data science? - Sep 4, 2018.
  
  An overview and discussion around data science, covering the history behind the term, data mining, statistical inference, machine learning, data engineering and more.

  Data Mining, Data Science, Decision Making, Statistics

• 5 Resources to Inspire Your Next Data Science Project - Sep 4, 2018.
  
  In this post, my intention is provide some useful tips and resources to springboard you into your next data science project.

  Data Science, Resources

• Financial Data Analysis – Data Processing 1: Loan Eligibility Prediction - Sep 4, 2018.
  
  In this first part I show how to clean and remove unnecessary features. Data processing is very time-consuming, but better data would produce a better model.

  Data Preprocessing, Data Processing, Finance, Python

• OLAP queries in SQL: A Refresher - Sep 3, 2018.
  
  Based on the recent book - Principles of Database Management - The Practical Guide to Storing, Managing and Analyzing Big and Small Data - this post examines how OLAP queries can be implemented in SQL.

  Bart Baesens, OLAP, SQL

• An End-to-End Project on Time Series Analysis and Forecasting with Python - Sep 3, 2018.
  
  Time series are widely used for non-stationary data, like economic, weather, stock price, and retail sales in this post. We will demonstrate different approaches for forecasting retail sales time series.

  Forecasting, Python, Time Series, Trend Detection

• Top Stories, Aug 27-Sep 2: Data Visualization Cheat Sheet; Topic Modeling with LSA, PLSA, LDA & lda2Vec - Sep 3, 2018.
  
  Also: AI Knowledge Map: How To Classify AI Technologies; How to Make Your Machine Learning Models Robust to Outliers; Linear Regression In Real Life; 5 Data Science Projects That Will Get You Hired in 2018

  Top stories

• Cartoon: Labor Day in the year 2050 - Sep 2, 2018.
  
  KDnuggets cartoon looks at how Labor Day can change in the year 2050.

  Cartoon, Labor Day, Robots