Supplement: Troubleshooting / Easier sharing of deep learning models and demos
cog
, "containers for machine learning."Supplement: Troubleshooting / Production, Deployment, MLOps
]]>More ways to "Dive into Machine Learning" / Aside: Bayesian Statistics and Machine Learning
Explore another notebook / What just happened?
Prof. Andrew Ng's Machine Learning on Coursera / Tips for this course
Getting Help: Questions, Answers, Chats / Some communities to know about!
Deep Learning / Easier sharing of deep learning models and demos
fastai/fastbook
by Jeremy Howard and Sylvain Gugger — "an introduction to deep learning, fastai and PyTorch."explosion/thinc
is an interesting library that wraps PyTorch, TensorFlow and MXNet models.Skilling up / Machine Learning and User Experience (UX)
More ways to "Dive into Machine Learning" / Aside: Bayesian Statistics and Machine Learning
]]>Supplement: Learning Pandas well / Some communities to know about!
pandas
and alternatives
Supplement: Troubleshooting / Some communities to know about!
Deep Learning / Easier sharing of deep learning models and demos
More Data Science materials / Machine Learning and User Experience (UX)
r0f1/datascience
— "A curated list of awesome resources for practicing data science using Python, including not only libraries, but also links to tutorials, code snippets, blog posts and talks."Deep Learning / Easier sharing of deep learning models and demos
labmlai/annotated_deep_learning_paper_implementations
— "Implementations/tutorials of deep learning papers with side-by-side notes." 50+ of them! Really nicely annotated and explained.Other courses / Take my tips with a grain of salt
microsoft/Data-Science-For-Beginners
— added in 2021 — "10-week, 20-lesson curriculum all about Data Science. Each lesson includes pre-lesson and post-lesson quizzes, written instructions to complete the lesson, a solution, and an assignment. Our project-based pedagogy allows you to learn while building, a proven way for new skills to 'stick'."ossu/data-science
(see also ossu/computer-science
)Deep Learning / Easier sharing of deep learning models and demos
Prof. Andrew Ng's Machine Learning on Coursera / Tips for this course
Prof. Andrew Ng's Machine Learning on Coursera / Tips for studying on a busy schedule
Other courses / Take my tips with a grain of salt
Deep Learning / Easier sharing of deep learning models and demos
Supplement: Troubleshooting / Risks - some starting points
Supplement: Troubleshooting / Risks - some starting points
]]>Tools you'll need / If you prefer local installation
Other courses / Take my tips with a grain of salt
Supplement: Learning Pandas well / Some communities to know about!
Supplement: Troubleshooting / Risks - some starting points
More Data Science materials / Aside: Bayesian Statistics and Machine Learning
Tools you'll need / Cloud-based options
Explore another notebook / What just happened?
Other courses / Take my tips with a grain of salt
Supplement: Learning Pandas well / Some communities to know about!
Supplement: Troubleshooting / Production, Deployment, MLOps
More Data Science materials / Machine Learning and User Experience (UX)
]]>Tools you'll need / Cloud-based options
Supplement: Learning Pandas well / Some communities to know about!
Supplement: Learning Pandas well / Some communities to know about!
Supplement: Learning Pandas well / Some communities to know about!