Top 23 Jupyter Notebook Machine Learning Projects
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A linear regression model
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Standing recommendation for beginners (we should eventually make a wiki) is https://madewithml.com/
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Scout APM
Scout APM: A developer's best friend. Try free for 14-days. Scout APM uses tracing logic that ties bottlenecks to source code so you know the exact line of code causing performance issues and can get back to building a great product faster.
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Project mention: Looking for buddy/mentor to study ML/datascience, with some focus on practical skills like cloud training and deployment | reddit.com/r/ProgrammingBuddies | 2021-11-29
I’m looking for a buddy to study the materials from these 2 Microsoft courses (or at least similar topics): - DS4Beginners - ML4Beginners
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Project mention: D I Refuse To Use Pytorch Because Its A Facebook | reddit.com/r/MachineLearning | 2020-12-29
Also, not a single docstring to document any code in the library - https://github.com/fastai/fastai/blob/master/fastai/vision/learner.py
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Project mention: Simulating trained model in Mujoco | reddit.com/r/reinforcementlearning | 2021-11-24
I am trying to replicate the results of this paper, which has its code on github. I'm new to Reinforcement Learning, and I do not know how to use the trained model to simulate the behavior in mujoco. If anyone could help me with this, it'd be helpful. Thanks!
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homemade-machine-learning
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
Project mention: Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained | reddit.com/r/MachineLearning | 2021-10-27 -
When using SHAP values in model explanation, we can measure the input features’ contribution to individual predictions. We won’t be covering the complex formulas to calculate SHAP values in this article, but we’ll show how to use the SHAP Python library to easily calculate SHAP values.
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Project mention: What is the most useful free course you have taken? | reddit.com/r/learnmachinelearning | 2021-11-23
fastai https://www.fast.ai/ it was a game changer for me also there is a lot of additional blogs from students that flesh the material even more, pretty active community with forums and discord server and very useful book that is great as reference (the book available as jupyter notebooks https://github.com/fastai/fastbook)
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The majority of this code is taken from the TensorFlow-Tutorials. I highly recommend them to those who want to get started with TensorFlow.
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Project mention: Would you rather use coding to analyze your data or use software (Tableau, PowerBI) that can do it for you? | reddit.com/r/datascience | 2021-10-30
A lot of good things said here about right tool for the job. One I really dig for certain scenarios are Pandas Profiling.
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to be fair, Swift for Tensorflow was dropped (Feb 21) way after this article was written (Aug 20) https://github.com/tensorflow/swift
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H2O
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
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cleverhans
An adversarial example library for constructing attacks, building defenses, and benchmarking both
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Project mention: Anyone willing to help me out on a discord call or something? | reddit.com/r/learnmachinelearning | 2021-05-27
This is the model I’m trying to understand and create my own version of: https://github.com/tensorflow/docs/blob/master/site/en/r1/tutorials/sequences/recurrent_quickdraw.md
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Project mention: Machine Learning for Trading: Notebooks, resources and references accompanying the book Machine Learning for Algorithmic Trading. Courses - star count:4384.0 | reddit.com/r/algoprojects | 2021-11-05
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Take a look at Pycaret python library. https://github.com/pycaret/pycaret
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Project mention: [D] Open source projects for interpretability | reddit.com/r/MachineLearning | 2021-04-28
You should check out Captum for PyTorch: https://captum.ai/ and tf-explain or lucid (this one is the framework used by distill) for Tensorflow although I think they are both oriented towards Vision interpretability (not sure if you are looking for that).
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There are scikit-learn (sklearn) API-compatible wrappers for e.g. PyTorch and TensorFlow.
Skorch: https://github.com/skorch-dev/skorch
tf.keras.wrappers.scikit_learn: https://www.tensorflow.org/api_docs/python/tf/keras/wrappers...
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t81_558_deep_learning
Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks
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A while back I open sourced a repository implementing fundamental machine learning algorithms in Python, along with the most important theoretical information. I originally created the repository for myself when preparing for AI residency interviews. You can find the original Reddit post here.
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Project mention: What is Probabilistic Programming? | reddit.com/r/learnmachinelearning | 2021-09-06
This tutorial explains what is probabilistic programming & provides a review of 5 frameworks (PPLs) using an example taken from Chapter 4 of Statistical Rethinking by Dr. Richard McElreath. Frameworks (PPLs) reviewed are - Stan (https://mc-stan.org/) PyMC3 (https://docs.pymc.io/) Tensorflow Probability (https://www.tensorflow.org/probability) Pyro/NumPyro (https://pyro.ai/) Turing.jl (https://turing.ml/stable/) I also provide the basic review of a great library called arviz (https://arviz-devs.github.io/arviz/), which can be used for all the above-mentioned PPLs to do Exploratory Data Analysis of Bayesian Models. Here is the link to the notebook in which I have implemented the example model using the above Frameworks/PPLs https://colab.research.google.com/drive/1zgR2b0j2waGi1ppnIe1rw7emkbBXtMqF?usp=sharing
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Looks like a nice project. I just bookmarked it to try sometime.
At a previous job, my boss wanted me to spend time on AutoML. I based my work on Google’s AdaNet [1] that did architecture search inside a single TensorFlow session. Unfortunately that project seems to have been abandoned.
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ISLR-python
An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code
Here or here for the Python versions of ISLR.
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Index
What are some of the best open-source Machine Learning projects in Jupyter Notebook? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | TensorFlow-Examples | 41,447 |
| 2 | MadeWithML | 29,164 |
| 3 | ML-For-Beginners | 27,641 |
| 4 | fastai | 21,674 |
| 5 | google-research | 20,618 |
| 6 | homemade-machine-learning | 18,554 |
| 7 | shap | 14,785 |
| 8 | fastbook | 13,911 |
| 9 | TensorFlow-Tutorials | 8,915 |
| 10 | pandas-profiling | 8,274 |
| 11 | swift | 6,038 |
| 12 | H2O | 5,637 |
| 13 | cleverhans | 5,330 |
| 14 | docs | 4,957 |
| 15 | machine-learning-for-trading | 4,882 |
| 16 | pycaret | 4,432 |
| 17 | lucid | 4,337 |
| 18 | skorch | 4,227 |
| 19 | t81_558_deep_learning | 4,107 |
| 20 | machine_learning_basics | 3,546 |
| 21 | probability | 3,544 |
| 22 | adanet | 3,342 |
| 23 | ISLR-python | 3,331 |
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