- Which Deep Learning Framework is Growing Fastest? - May 1, 2019.
In September 2018, I compared all the major deep learning frameworks in terms of demand, usage, and popularity. TensorFlow was the champion of deep learning frameworks and PyTorch was the youngest framework. How has the landscape changed?
Tags: Data Science, Data Scientist, Deep Learning, fast.ai, Keras, Python, PyTorch, TensorFlow
- Building NLP Classifiers Cheaply With Transfer Learning and Weak Supervision - Mar 15, 2019.
In this blog, I’ll walk you through a personal project in which I cheaply built a classifier to detect anti-semitic tweets, with no public dataset available, by combining weak supervision and transfer learning.
Pages: 1 2
Tags: Bias, fast.ai, NLP, Python, Text Classification, Transfer Learning, Twitter, ULMFiT
- The 6 Most Useful Machine Learning Projects of 2018 - Jan 15, 2019.
Let’s take a look at the top 6 most practically useful ML projects over the past year. These projects have published code and datasets that allow individual developers and smaller teams to learn and immediately create value.
Tags: Automated Machine Learning, Facebook, fast.ai, Google, Keras, Machine Learning, Object Detection, Python, Reinforcement Learning, Word Embeddings
10 Free Must-See Courses for Machine Learning and Data Science - Nov 8, 2018.
Check out a collection of free machine learning and data science courses to kick off your winter learning season.
Tags: Data Science, Deep Learning, fast.ai, Google, Linear Algebra, Machine Learning, MIT, NLP, Reinforcement Learning, Stanford, Yandex
GitHub Python Data Science Spotlight: High Level Machine Learning & NLP, Ensembles, Command Line Viz & Docker Made Easy - Oct 16, 2018.
This post spotlights 5 data science projects, all of which are open source and are present on GitHub repositories, focusing on high level machine learning libraries and low level support tools.
Tags: Data Science, Docker, Ensemble Methods, fast.ai, GitHub, Machine Learning, NLP, Python
- Deep Learning Framework Power Scores 2018 - Sep 24, 2018.
Who’s on top in usage, interest, and popularity?
Tags: CNTK, Deep Learning, fast.ai, Java, Keras, MXNet, Python, PyTorch, TensorFlow, Theano
- Top KDnuggets tweets, Jul 18-24: Causation in a Nutshell - Jul 25, 2018.
Also fast.ai Deep Learning Part 2 Complete Course Notes; Comparison of Top 6 Python #NLProc Libraries.
Tags: Causation, Deep Learning, fast.ai, Top tweets
- 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.
Tags: Deep Learning, fast.ai, Jeremy Howard, MOOC
- Top KDnuggets tweets, Jul 4-10: Fantastic notes on the freely available @fastdotai machine learning course - Jul 11, 2018.
Also: Analyze a Soccer (Football) Game Using #Tensorflow Object Detection; 18 Inspiring Women In AI, Big Data, Data Science, Machine Learning; Timsort - the fastest #sorting #algorithm you've never heard of.
Tags: fast.ai, Football, Machine Learning, Soccer, TensorFlow, Top tweets
- 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.
Tags: Deep Learning, fast.ai, Jeremy Howard, MOOC
- 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.
Tags: fast.ai, Jeremy Howard, Machine Learning, MOOC
- An Introduction to Deep Learning for Tabular Data - May 17, 2018.
This post will discuss a technique that many people don’t even realize is possible: the use of deep learning for tabular data, and in particular, the creation of embeddings for categorical variables.
Tags: Deep Learning, fast.ai, Kaggle, Neural Networks, word2vec
- 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.
Tags: fast.ai, GitHub, Jeremy Howard, Open Source, Python, scikit-learn
- Quick Feature Engineering with Dates Using fast.ai - Mar 16, 2018.
The fast.ai library is a collection of supplementary wrappers for a host of popular machine learning libraries, designed to remove the necessity of writing your own functions to take care of some repetitive tasks in a machine learning workflow.
Tags: fast.ai, Feature Engineering, Machine Learning, Pandas, Python, Time Series
- How to do Machine Learning Efficiently - Mar 13, 2018.
I now believe that there is an art, or craftsmanship, to structuring machine learning work and none of the math heavy books I tended to binge on seem to mention this.
Tags: Architecture, fast.ai, Machine Learning, Validation, Workflow
- KDnuggets™ News 18:n07, Feb 14: 5 Machine Learning Projects You Should Not Overlook; Intro to Python Ensembles - Feb 14, 2018.
5 Machine Learning Projects You Should Not Overlook; Introduction to Python Ensembles; Which Machine Learning Algorithm be used in year 2118?; Fast.ai Lesson 1 on Google Colab (Free GPU)
Tags: Algorithms, CoLaboratory, Data Science, Ensemble Methods, fast.ai, Feature Engineering, Machine Learning, Python, Scala
- Fast.ai Lesson 1 on Google Colab (Free GPU) - Feb 8, 2018.
In this post, I will demonstrate how to use Google Colab for fastai. You can use GPU as a backend for free for 12 hours at a time. GPU compute for free? Are you kidding me?
Tags: CoLaboratory, Deep Learning, fast.ai, Google, GPU, Jupyter
5 Fantastic Practical Machine Learning Resources - Feb 6, 2018.
This post presents 5 fantastic practical machine learning resources, covering machine learning right from basics, as well as coding algorithms from scratch and using particular deep learning frameworks.
Tags: Deep Learning, fast.ai, Gluon, Machine Learning, MOOC, MXNet, Python
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.
Tags: Andrew Ng, Coursera, Deep Learning, deeplearning.ai, fast.ai, Jeremy Howard, Neural Networks
- 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.
Tags: AI, fast.ai, Hype, Jeremy Howard, Research, Twitter, Zeynep Tufekci
- 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.
Tags: AI, Australia, Automation, Deep Learning, Enlitic, fast.ai, Healthcare, Jeremy Howard, Kaggle
- 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.
Tags: AWS, Deep Learning, fast.ai, Jeremy Howard, Kaggle, MOOC
7 Steps to Mastering SQL for Data Science — 2019 Edition