- Deep Learning for Coders with fastai and PyTorch: The Free eBook - Jun 1, 2020.
If you are interested in a top-down, example-driven book on deep learning, check out the draft of the upcoming Deep Learning for Coders with fastai & PyTorch from fast.ai team.
- 12 Deep Learning Researchers and Leaders - Sep 23, 2019.
Our list of deep learning researchers and industry leaders are the people you should follow to stay current with this wildly expanding field in AI. From early practitioners and established academics to entrepreneurs and today’s top corporate influencers, this diverse group of individuals is leading the way into tomorrow’s deep learning landscape.
- 12 NLP Researchers, Practitioners & Innovators You Should Be Following - Aug 12, 2019.
Check out this list of NLP researchers, practitioners and innovators you should be following, including academics, practitioners, developers, entrepreneurs, and more.
- 10 New Things I Learnt from fast.ai Course V3 - Jun 24, 2019.
Fastai offers some really good courses in machine learning and deep learning for programmers. I recently took their "Practical Deep Learning for Coders" course and found it really interesting. Here are my learnings from the course.
- fast.ai Deep Learning Part 2 Complete Course Notes - Jul 17, 2018.
This posts is a collection of a set of fantastic notes on the fast.ai deep learning part 2 MOOC freely available online, as written and shared by a student. These notes are a valuable learning resource either as a supplement to the courseware or on their own.
- fast.ai Deep Learning Part 1 Complete Course Notes - Jul 10, 2018.
This posts is a collection of a set of fantastic notes on the fast.ai deep learning part 1 MOOC freely available online, as written and shared by a student. These notes are a valuable learning resource either as a supplement to the courseware or on their own.
- fast.ai Machine Learning Course Notes - Jul 6, 2018.
This posts is a collection of a set of fantastic notes on the fast.ai machine learning MOOC freely available online, as written and shared by a student. These notes are a valuable learning resource either as a supplement to the courseware or on their own.
- How I Unknowingly Contributed To Open Source - Apr 24, 2018.
This article explains what is meant by the term 'open source' and why all data scientists should be a part of it.
- An Overview of 3 Popular Courses on Deep Learning - Oct 13, 2017.
After completing the 3 most popular MOOCS in deep learning from Fast.ai, deeplearning.ai/Coursera (which is not completely released) and Udacity, I believe a post about what you can expect from these 3 courses will be useful for future Deep learning enthusiasts.
- Credible Sources of Accurate Information About AI - Oct 9, 2017.
I want to recommend several credible sources of accurate information. Most of the writing on this list is intended to be accessible to anyone—even if you aren’t a programmer or don’t work in tech.
- Top KDnuggets tweets, Sep 06-12: Visualizing Cross-validation Code; Intro to #Blockchain and #BigData - Sep 13, 2017.
Also: WTF #Python - A collection of interesting and tricky Python examples; Thoughts after taking @AndrewYNg #Deeplearning #ai course; Another #Keras Tutorial For #NeuralNetwork Beginners.
- Exclusive: Interview with Jeremy Howard on Deep Learning, Kaggle, Data Science, and more - Jan 14, 2017.
My exclusive interview with rock star Data Scientist Jeremy Howard, on his latest Deep Learning course, what is needed for success in Kaggle, how Enlitic is transforming medical diagnostics, and what Data Scientists should do to create value for their organization.
- KDnuggets™ News 16:n46, Dec 28: 4 Reasons Your Machine Learning Model is Wrong; Deep Learning for coders MOOC - Dec 28, 2016.
First Deep Learning for coders MOOC launched by Jeremy Howard; 4 Reasons Your Machine Learning Model is Wrong; 5 Capability Levels of Deep Learning Intelligence; Data Science Basics: Power Laws and Distributions.
- First Deep Learning for coders MOOC launched by Jeremy Howard - Dec 21, 2016.
Leading Data Scientist and entrepreneur Jeremy Howard launches a free Deep Learning course that shows end-to-end how to get state of the art results, including a top place in a Kaggle competition.
- Should Data Science Really Do That? - May 13, 2015.
Data Science amazing progress in its ability to do predictions and analysis is raising important ethical questions, such as should that data be collected? Should the collected data be used for that application? Should you be involved?
- Top KDnuggets tweets, Dec 15-16: KDnuggets Cartoon: Unexpected Machine Learning Recommendations - Dec 17, 2014.
KDnuggets Cartoon: Unexpected Machine Learning Recommendations; Review: #DataScience at the Command Line - great book; Most Demanded Data Science and Data Mining Skills; The problem is that many ML researchers are not working on on most impactful areas.
- Top KDnuggets tweets, Aug 29-31: Data Analytics vs Predictive Modeling vs …; 100 top machine learning talks - Sep 1, 2014.
Data Analytics vs Predictive Modeling vs Data Mining vs Big Data; 100 most popular machine learning talks at videolectures; Intro to parallel iterative Deep Learning on Hadoop YARN; Jeremy Howard answers why he left Kaggle and what are his plans now.