100-days-of-ml-code

100 Days of ML Coding

360_assgn

365-days-daily-coding-challenge

aaamlp-cn

Approaching (Almost) Any Machine Learning Problem中译版，在线文档地址：https://ytzfhqs.github.io/AAAMLP-CN/

accelerated-data-lake

A packaged Data Lake solution, that builds a highly functional Data Lake, with a data catalog queryable via Elasticsearch

ai-102-aiengineer

Lab files for AI-102 - AI Engineer

ai-mancala-game-design

Implemented Greedy,Minimax and Alpha Beta Algorithm in Python to select best moves for each player by looking n steps ahead.

ailearning

AiLearning：数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2

airbyte

Data integration platform for ELT pipelines from APIs, databases & files to warehouses & lakes.

amazon-textract-transformer-pipeline

Post-process Amazon Textract results with Hugging Face transformer models for document understanding

analytical-tutorials

Tutorials for writing analytical scripts

apachespark

This repository will help you to learn about databricks concept with the help of examples. It will include all the important topics which we need in our real life experience as a data engineer. We will be using pyspark & sparksql for the development. At the end of the course we also cover few case studies.

applyingml

📌 Papers, guides, and mentor interviews on applying machine learning for ApplyingML.com—the ghost knowledge of machine learning.

aqi-prediction-spark-ml

This project is to prove the efficiency of distributed computing and distributed database. The machine learning multiple classification algorithms in spark were used to predict the Air Quality Index in California.

architecture-center

Open Source documentation for the Azure Architecture Center on Microsoft Docs

association-rules-book-dataset-using-python

Prepare rules for the all the data sets 1) Try different values of support and confidence. Observe the change in number of rules for different support,confidence values 2) Change the minimum length in apriori algorithm 3) Visulize the obtained rules using different plots

association-rules-book-dataset-using-r

Prepare rules for the all the data sets 1) Try different values of support and confidence. Observe the change in number of rules for different support,confidence values 2) Change the minimum length in apriori algorithm 3) Visulize the obtained rules using different plots

association-rules-movies-dataset-using-python

Prepare rules for the all the data sets 1) Try different values of support and confidence. Observe the change in number of rules for different support,confidence values 2) Change the minimum length in apriori algorithm 3) Visulize the obtained rules using different plots

association-rules-movies-dataset-using-r

Prepare rules for the all the data sets 1) Try different values of support and confidence. Observe the change in number of rules for different support,confidence values 2) Change the minimum length in apriori algorithm 3) Visulize the obtained rules using different plots

awesome-chatbot

Awesome Chatbot Projects,Corpus,Papers,Tutorials.Chinese Chatbot =>:

awesome-computer-vision

A curated list of awesome computer vision resources

awesome-distributed-ml

A curated list of awesome projects and papers for distributed training or inference

awesome-gemini

A collection of awesome things regarding the gemini protocol ecosystem.

awesome-generative-ai

A curated list of modern Generative Artificial Intelligence projects and services

awesome-llm-and-aigc

🔥🔥🔥A collection of some awesome public projects about Large Language Model, Vision Foundation Model and AI Generated Content.

awesome-mlops

A curated list of references for MLOps

awesome-python-applications

💿 Free software that works great, and also happens to be open-source Python.

awesome-transformer-nlp

A curated list of NLP resources focused on Transformer networks, attention mechanism, GPT, BERT, ChatGPT, LLMs, and transfer learning.

awesome-yolo-object-detection

🚀🚀🚀 A collection of some awesome public YOLO object detection series projects.

aws-glue-pyspark-etl-job

A Pyspark job to handle upserts, conversion to parquet and create partitions on S3