Awesome List Updates on Aug 31, 2019

4 awesome lists updated today.

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1. Awesome Machine Learning

Go / General-Purpose Machine Learning

• go-dnn (⭐8) - Deep Neural Networks for Golang (powered by MXNet)

2. Awesome Aws

Open Source Repos / Glacier

• vsespb/mt-aws-glacier 🔥🔥🔥 (⭐539) - Perl Multithreaded Multipart sync to Glacier.

3. Awesome Ruby

Database Tools

• Rein (⭐669) - Database constraints made easy for ActiveRecord.

4. Awesome Python Data Science

Machine Learning / General Purpose Machine Learning

• scikit-learn - Machine learning in Python.

• cuML (⭐4.8k) - RAPIDS Machine Learning Library.

• modAL (⭐2.3k) - Modular active learning framework for Python3.

• Sparkit-learn (⭐1.2k) - PySpark + scikit-learn = Sparkit-learn.

• MLxtend (⭐5k) - Extension and helper modules for Python's data analysis and machine learning libraries.

• Reproducible Experiment Platform (REP) (⭐696) - Machine Learning toolbox for Humans.

• scikit-multilearn (⭐939) - Multi-label classification for python.

• seqlearn (⭐697) - Sequence classification toolkit for Python.

• pystruct (⭐668) - Simple structured learning framework for Python.

• RuleFit (⭐422) - Implementation of the rulefit.

• metric-learn (⭐1.4k) - Metric learning algorithms in Python.

Machine Learning / Ensemble Methods

• ML-Ensemble - High performance ensemble learning.

• stacked_generalization (⭐117) - Library for machine learning stacking generalization.

• vecstack (⭐692) - Python package for stacking (machine learning technique).

Machine Learning / Imbalanced Datasets

• imbalanced-algorithms (⭐239) - Python-based implementations of algorithms for learning on imbalanced data.

Machine Learning / Random Forests

• rpforest (⭐224) - A forest of random projection trees.

• sklearn-random-bits-forest (⭐9) - Wrapper of the Random Bits Forest program written by (Wang et al., 2016).

• rgf_python (⭐381) - Python Wrapper of Regularized Greedy Forest.

Machine Learning / Kernel Methods

• pyFM (⭐926) - Factorization machines in python.

• fastFM (⭐1.1k) - A library for Factorization Machines.

• tffm (⭐781) - TensorFlow implementation of an arbitrary order Factorization Machine.

• scikit-rvm (⭐238) - Relevance Vector Machine implementation using the scikit-learn API.

• ThunderSVM (⭐1.6k) - A fast SVM Library on GPUs and CPUs.

Deep Learning / PyTorch

• PyTorch (⭐91k) - Tensors and Dynamic neural networks in Python with strong GPU acceleration.

• ignite (⭐4.7k) - High-level library to help with training neural networks in PyTorch.

Deep Learning / TensorFlow

• TensorFlow (⭐191k) - Computation using data flow graphs for scalable machine learning by Google.

• TensorLayer (⭐7.4k) - Deep Learning and Reinforcement Learning Library for Researcher and Engineer.

• TFLearn (⭐9.6k) - Deep learning library featuring a higher-level API for TensorFlow.

• Sonnet (⭐9.9k) - TensorFlow-based neural network library.

• Polyaxon (⭐3.7k) - A platform that helps you build, manage and monitor deep learning models.

• tensorflow-upstream (⭐694) - TensorFlow ROCm port.

• TensorFlow Fold (⭐1.8k) - Deep learning with dynamic computation graphs in TensorFlow.

• TensorLight (⭐11) - A high-level framework for TensorFlow.

• Mesh TensorFlow (⭐1.6k) - Model Parallelism Made Easier.

Model Explanation / Others

• Contrastive Explanation (⭐44) - Contrastive Explanation (Foil Trees).

• yellowbrick (⭐4.4k) - Visual analysis and diagnostic tools to facilitate machine learning model selection.

• scikit-plot (⭐2.4k) - An intuitive library to add plotting functionality to scikit-learn objects.

• shap (⭐24k) - A unified approach to explain the output of any machine learning model.

• Lime (⭐12k) - Explaining the predictions of any machine learning classifier.

• FairML (⭐364) - FairML is a python toolbox auditing the machine learning models for bias.

• model-analysis (⭐1.3k) - Model analysis tools for TensorFlow.

• themis-ml (⭐126) - A library that implements fairness-aware machine learning algorithms.

• treeinterpreter (⭐759) - Interpreting scikit-learn's decision tree and random forest predictions.

Genetic Programming / Others

• gplearn (⭐1.7k) - Genetic Programming in Python.

• karoo_gp (⭐164) - A Genetic Programming platform for Python with GPU support.

• sklearn-genetic (⭐322) - Genetic feature selection module for scikit-learn.

Optimization / Others

• BoTorch (⭐3.3k) - Bayesian optimization in PyTorch.

• hyperopt-sklearn (⭐1.6k) - Hyper-parameter optimization for sklearn.

• sklearn-deap (⭐774) - Use evolutionary algorithms instead of gridsearch in scikit-learn.

• sigopt_sklearn (⭐75) - SigOpt wrappers for scikit-learn methods.

• GPflowOpt (⭐272) - Bayesian Optimization using GPflow.

Statistics / NLP

• pandas_summary (⭐519) - Extension to pandas dataframes describe function.

• Pandas Profiling (⭐13k) - Create HTML profiling reports from pandas DataFrame objects.

• Alphalens (⭐3.8k) - Performance analysis of predictive (alpha) stock factors.

Computations / Synthetic Data

• Dask (⭐13k) - Parallel computing with task scheduling.

Spatial Analysis / Synthetic Data

• GeoPandas (⭐4.8k) - Python tools for geographic data.

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