dsninja Goto Github PK

databricks-academy-demo

datascience-r

Docker image for R.

dbcallms

Notebooks for Large Language Models (LLMs) Specialization

docker-network-tools

A Docker image with various network tools pre-installed.

docker-stacks

Ready-to-run Docker images containing Jupyter applications

dsninja

Config files for my GitHub profile.

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

ice_breaker

jsonresume-gpt3

Fake JSON Resumes generated with GPT-3

kaggle-march-madness-machine-learning-2018

Kaggle machine learning competition submission for March Madness 2018

learning-apache-spark

Notes on Apache Spark (pyspark)

learningapachespark

LearningApacheSpark

machine-learning-with-python

Python code for common Machine Learning Algorithms

mmml2022

mrpcasestudy

An introduction to Multilevel Modeling and Poststratification (MRP) and some of its extensions.

nanogpt

The simplest, fastest repository for training/finetuning medium-sized GPTs.

persson_ml_collection

A resource for learning about Machine learning & Deep Learning

picogpt

An unnecessarily tiny implementation of GPT-2 in NumPy.

pyspark-and-mllib

Getting start with PySpark and MLlib

pythondatasciencehandbook

Python Data Science Handbook: full text in Jupyter Notebooks

pythononeliners

This repository collects all interesting Python one-liners. Feel free to submit yours!

pytorchtutorial

PyTorch Tutorials from my YouTube channel

pytorchtutorials

PyTorch tutorials.

sbnlp

自然语言处理（NLP）教程，包括：词向量，词法分析，预训练语言模型，文本分类，文本语义匹配，信息抽取，翻译，对话。

scikit-learn-cookbook-second-edition

scikit-learn Cookbook Second Edition, published by Packt

simpleapp

spark

Apache Spark - A unified analytics engine for large-scale data processing

streamlit_freecodecamp

Build 12 Data Apps in Python with Streamlit

testmd

trekhleb-learn-python

📚 Playground and cheatsheet for learning Python. Collection of Python scripts that are split by topics and contain code examples with explanations.