2228 Open source projects that are alternatives of or similar to Arch-Data-Science

Tests and benchmarks for cudnn (and in the future, other nvidia libraries)

NumPy & SciPy for GPU

Ubuntu 18.04 How to install Nvidia driver + CUDA + CUDNN + build tensorflow for gpu step by step command line

Minimal Deep Learning library is written in Python/Cython/C++ and Numpy/CUDA/cuDNN.

TensorFlow wheels built for latest CUDA/CuDNN and enabled performance flags: SSE, AVX, FMA; XLA

cuDF - GPU DataFrame Library

A python library for decision tree visualization and model interpretation.

Use AI to generate a optimized stock portfolio

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Serve scikit-learn, XGBoost, TensorFlow, and PyTorch models with AWS Lambda container images support.

Open source guides/codes for mastering deep learning to deploying deep learning in production in PyTorch, Python, C++ and more.

Minimal runtime core of Caffe, Forward only, GPU support and Memory efficiency.

Earthquake Prediction Challenge with LightGBM and XGBoost

AsyncIO serving for data science models

Otto makes machine learning an intuitive, natural language experience. 🏆 Facebook AI Hackathon winner ⭐️ #1 Trending on MadeWithML.com ⭐️ #4 Trending JavaScript Project on GitHub ⭐️ #15 Trending (All Languages) on GitHub

🔮 A refreshing functional take on deep learning, compatible with your favorite libraries

🌳 Stacked Gradient Boosting Machines

Kaggle Kernels (Python, R, Jupyter Notebooks)

Algorithmic trading using machine learning.

A collection of notebooks of my Machine Learning class written in python 3

Open Machine Learning Course

👑 Python factor analysis library (PCA, CA, MCA, MFA, FAMD)

Disease Prediction based on Symptoms.

Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springer.

Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.

Parallel computing with task scheduling

도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.

Quora Kaggle Competition : Natural Language Processing using word2vec embeddings, scikit-learn and xgboost for training

도서 "[개정판] 파이썬 라이브러리를 활용한 머신 러닝"의 주피터 노트북과 코드입니다.

A hyperparameter optimization and data collection toolbox for convenient and fast prototyping of machine-learning models.

A jupyter notebook having all most frequent used code snippet for daily data scienceoperations

Kaggle Struggle

Conversational text Analysis using various NLP techniques

Predicting Profitable Day Trading Positions using Decision Tree Classifiers. scikit-learn | Flask | SQLite3 | pandas | MLflow | Heroku | Streamlit

Machine Learning University: Decision Trees and Ensemble Methods

All the slides, accompanying code and exercises all stored in this repo. 🎈

🍊 📊 💡 Orange: Interactive data analysis

Stacked Generalization (Ensemble Learning)

머신러닝/딥러닝(PyTorch, TensorFlow) 전용 도커입니다. 한글 폰트, 한글 자연어처리 패키지(konlpy), 형태소 분석기, Timezone 등의 설정 등을 추가 하였습니다.

central pacman cache

A 100%-Julia implementation of Gradient-Boosting Regression Tree algorithms

NLP made easy

📒 Experiment tracking tool and model registry

Extensive tutorials for the Advanced NLP Workshop in Open Data Science Conference Europe 2020. We will leverage machine learning, deep learning and deep transfer learning to learn and solve popular tasks using NLP including NER, Classification, Recommendation \ Information Retrieval, Summarization, Classification, Language Translation, Q&A and T…

📚 Various cheatsheets in PDF

Machine Learning for Spot Prices

⭐ An anomaly-based intrusion detection system.

Top 1% rankings (22/3270) code sharing for Kaggle competition Sberbank Russian Housing Market: https://www.kaggle.com/c/sberbank-russian-housing-market

A collection of ML related stuff including notebooks, codes and a curated list of various useful resources such as books and softwares. Almost everything mentioned here is free (as speech not free food) or open-source.

Predict people interest in renting specific NYC apartments. The challenge combines structured data, geolocalization, time data, free text and images.

My dataquest project solutions

This is the final project for the Udacity Machine Learning Nanodegree: Predicting article retweets and likes based on the title using Machine Learning

Tools that make working with scikit-learn and pandas easier.

2017第一届腾讯社交广告高校算法大赛Rank28_code

Tutoriais de Python, Data Science, Machine Learning e Deep Learning - Sigmoidal

텐서플로우와 머신러닝으로 시작하는 자연어처리(로지스틱회귀부터 트랜스포머 챗봇까지)

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

Scalable machine 🤖 learning for time series forecasting.

The complete code and notebooks used for the ACM Recommender Systems Challenge 2019

Social Distancing and Face Mask Detection using TensorFlow. Install all required Libraries and GPU drivers as well. Refer to README.md or REPORT for know to installation requirement