100 Days of ML Coding
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Updated
Jul 15, 2020
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scikit-learn is a widely-used Python module for classic machine learning. It is built on top of SciPy.
100 Days of ML Coding
AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP
Python Data Science Handbook: full text in Jupyter Notebooks
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
The "Python Machine Learning (1st edition)" book code repository and info resource
Dive into Machine Learning with Python Jupyter notebook and scikit-learn!
Spawned off https://github.com/onnx/onnx/pull/2772/files/7ab93cc1b635eada330dae7424d4ff7e8c22c295#r440422245, opening issue to track resolution
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
The documentation in the Joins section https://docs.dask.org/en/latest/dataframe-joins.html has code blocks but they aren't interactive and therefore not as useful.
I think the documentation would benefit from an interactive example with use of real data (or data from the demo API).
I had a quick rummage of the tutorial (h
Open Machine Learning Course
The "Python Machine Learning (2nd edition)" book code repository and info resource
For example, if there is a relationship transaction.session_id -> sessions.id and we are calculating a feature transactions: sessions.SUM(transactions.value) any rows for which there is no corresponding session should be given the default value of 0 instead of NaN.
Of course this should not normally occur, but when it does it seems more reasonable to use the default_value.
`DirectF
with the Power Transformer.
My blogs and code for machine learning. http://cnblogs.com/pinard
PipelineAI Kubeflow Distribution
I see the code
device = ‘cuda’ if torch.cuda.is_available() else ‘cpu’
repeated often in user code. Maybe we should introduce device='auto' exactly for this case?
Yes
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
Jupyter notebooks from the scikit-learn video series
Visual analysis and diagnostic tools to facilitate machine learning model selection.
AutoGluon: AutoML Toolkit for Deep Learning
A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.
A library for debugging/inspecting machine learning classifiers and explaining their predictions
I think it could be useful, when one wants to plot only e.g. class 1, to have an option to produce consistent plots for both plot_cumulative_gain and plot_roc
At the moment, instead, only plot_roc supports such option.
Thanks a lot
Support DataFrame.select_dtypes
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference
Created by David Cournapeau
Released January 05, 2010
Latest release about 1 month ago