The 30 Days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than 100 days. Follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
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Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Best Practices on Recommendation Systems
- machine-learning
- recommender
- ranking
- deep-learning
A straightforward method for training your LLM, from downloading data to generating text.
Translated🔍 Hands-on LLM Application Development, Part 1: A Full-Stack Guide to RAG Technology. Read online at: https://datawhalechina.github.io/all-in-rag/
- embedding
- kimi-k2
- langchain
- llama-index
A collection of machine learning examples and tutorials.
TranslatedBig data analysis project
- python
- sql
- hql
The process of extracting product data from Amazon using Python, including titles, ratings, prices, images, and descriptions.
- amazon
- amazon-scraper
- python
- web-scraper
Learn step-by-step how to scrape Google Trends data and make a result comparison using Python and Oxylabs SERP API. Extract keywords, their popularity, breakdown by region, related queries, and more.
- google-trend
- google-trend-api
- google-trend-strategy
Reproducing and studying RL algorithms for LLM agents, including GRPO, GSPO, DAPO, OPD, Search-R1, ReTool, ALFWorld and beyond.
- agent-rl
- dapo
- gspo
- opd
Auto-optimizing a neural net (and its architecture) on the CIFAR-100 dataset. Could be easily transferred to another dataset or another classification task.
- hyperopt
- hyperparameter-optimization
- hyperparameter-tuning
- hyperparameters-optimization