wangjiahong's Stars
philbot9/youtube-info
Fetch meta information about YouTube videos
bdanalytics/Berkeley-Spark
edX:Berkeley:Spark
hougs/ds-for-telco
Source material for Data Science for Telecom Tutorial at Strata Singapore 2015
intel-analytics/ipex-llm
Accelerate local LLM inference and finetuning (LLaMA, Mistral, ChatGLM, Qwen, Baichuan, Mixtral, Gemma, Phi, MiniCPM, etc.) on Intel XPU (e.g., local PC with iGPU and NPU, discrete GPU such as Arc, Flex and Max); seamlessly integrate with llama.cpp, Ollama, HuggingFace, LangChain, LlamaIndex, GraphRAG, DeepSpeed, vLLM, FastChat, Axolotl, etc.
spotify/luigi
Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
jakevdp/sklearn_pycon2015
Materials for my Pycon 2015 scikit-learn tutorial.
databricks/learning-spark
Example code from Learning Spark book
adarsh0806/cs105
BerkeleyX: CS105x Introduction to Apache Spark
dipanjanS/BerkeleyX-CS190.1x-Scalable-Machine-Learning
This repository contains code files specifically IPython notebooks for the assignments in the course "Scalable Machine Learning" by UC Berkeley and Databricks on edX
apache/zeppelin
Web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala and more.
mGalarnyk/Python_Tutorials
Python tutorials in both Jupyter Notebook and youtube format.
ParrotPrediction/docker-course-xgboost
Materials for an online-course - "Practical XGBoost in Python"
marcotcr/lime
Lime: Explaining the predictions of any machine learning classifier
cs109/2015lab1
amueller/introduction_to_ml_with_python
Notebooks and code for the book "Introduction to Machine Learning with Python"
wesm/pydata-book
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
VowpalWabbit/vowpal_wabbit
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
deeplearning4j/deeplearning4j
Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learn...
wangjiahong/data-science-ipython-notebooks
Continually updated data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines. https://bit.ly/data-notes
scikit-learn-contrib/hdbscan
A high performance implementation of HDBSCAN clustering.
jtoy/awesome-tensorflow
TensorFlow - A curated list of dedicated resources http://tensorflow.org
amazon-archives/amazon-dsstne
Deep Scalable Sparse Tensor Network Engine (DSSTNE) is an Amazon developed library for building Deep Learning (DL) machine learning (ML) models
wangjiahong/ISLR-python
An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013) : Python code
IRkernel/IRkernel
R kernel for Jupyter
wangjiahong/2015
Public material for CS109