• Maps of the Brain
  A century of cortical cartography has helped neurologists understand how the human brain perceives and interprets our complex surroundings...

• Human-Machine Work Teams
  “As the future of work spans from lightly technology-augmented employees all the way up to full job replacement by robots, the workforce will increasingly become a hybrid of humans and machines,” writes Gownder in conclusion. “Human-machine teaming… will grow into a key workforce technology discipline.” Companies should keep in mind that...

• Understanding Deep Learning for Object Detection
  In this blog post, I will explore important work in deep learning for object detection. I will introduce how those methods evolved over time and compare their differences and similarities. By showing innovations and limitations of each method and how later methods progress to solve previous problems, you will see — which is quite interesting — that research gets improved each time by just a small but elegant adjustment...

 
Gain better insights from your data with A Guide to Data Science at Scale

Wondering how big data can help you drive innovation? The most successful businesses don't necessarily have the most data, but they definitely extract the most insightful findings from their data. See how easy it is to build and scale ML models with a unified analytics platform. Find out how to collaborate across data teams to uncover insights faster and learn how companies like Shell and Hotels.com use big data and AI to drive innovation. Download this free Databricks eBook, A Guide to Data Science at Scale, to learn more.
   

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• Attacks against machine learning — an overview
  This blog post survey the attacks techniques that target AI (artificial intelligence) systems and how to protect against them...

• Building a Question-Answering System from Scratch— Part 1
  First part of the series focusses on Facebook Sentence Embedding...

• Data Science Leaders: There are too many of you
  Today I spoke at a summit for leaders in data science (the discipline that spans machine learning, artificial intelligence, statistics, data summarization, and visualization). As I looked over at the sea of faces belonging to the brightest trailblazers guiding today’s data science teams, I found myself thinking, “There are too many of you.”...

• How To Create a ChatBot With tf-seq2seq For Free!
  tf-seq2seq is a new framework based on TensorFlow that can be used for a variety of tasks where seq2seq models are useful...

• Starting a Second Machine Learning Tools Company, Ten Years Later
  I’ve spent the last six months heads down building a new machine learning tool called Weights and Biases with my longtime cofounder Chris Van Pelt, my new cofounder and friend Shawn Lewis and brave early users at Open AI, Toyota Research, Uber and others. Now that it’s public I wanted to talk a little bit about why I’m (still) so excited about building machine learning tools...

• Learning Disentangled Joint Continuous and Discrete Representations
  This repo contains an implementation of JointVAE, a framework for jointly disentangling continuous and discrete factors of variation in data in an unsupervised manner...

• Relational inductive biases, deep learning, and graph networks
  The following is part position paper, part review, and part unification. We argue that combinatorial generalization must be a top priority for AI to achieve human-like abilities, and that structured representations and computations are key to realizing this objective...

• DeepPhys: Video-Based Physiological Measurement Using Convolutional Attention Networks
  Non-contact video-based physiological measurement has many applications in health care and human-computer interaction. Practical applications require measurements to be accurate even in the presence of large head rotations. We propose the first end-to-end system for video-based measurement of heart and breathing rate using a deep convolutional network...

• Launch TensorFlow TensorBoard
  Learn how to use the TensorBoard command line utility to launch the TensorFlow TensorBoard web service, via a screencast video and full tutorial transcript...

• Introducing MLflow: an Open Source Machine Learning Platform
  Mlflow is still currently in alpha, but we believe that it already offers a useful framework to work with ML code, and we would love to hear your feedback. In this post, we’ll introduce MLflow in detail and explain its components...

• Improving Deep Learning Performance with AutoAugment
  AutoAugment is an automatic way to design custom data augmentation policies for computer vision datasets, e.g., guiding the selection of basic image transformation operations, such as flipping an image horizontally/vertically, rotating an image, changing the color of an image, etc...

• Test-Driven Machine Learning
  The book begins with an introduction to test-driven machine learning and quantifying model quality. From there, you will test a neural network, predict values with regression, and build upon regression techniques with logistic regression...
  
  For a detailed list of books covering Data Science, Machine Learning, AI and associated programming languages check out our resources page...