Data Science
- NLP key terms explained!
- Neptune.ai tips and tricks from image segmentation
- Stream-lit deployment of ML models
- AI searchable video library
- Streamlit interacive dashboards
- Deal with missing values
- How to start NLP project
- NLP Best Practices by Microsoft 👌
- ML Tech Debt
- Quick Deployment using Streamlit 🔥
- Pytorch Official Tutorials
- Financial Machine Learning by Hudson and Thames
- David Robinson Live Coding
- Nice Coding Habits for DS
- 10 useful ML practices
- Model Evaluation Metrics
- Plotly Dashboard
- ML in Production ⬅ Read all the guidelines
- Useful Python Site- RealPython 💗
- Basic Definitions of Models
- Handling Missing Values
- Project Euler
- Markdown Basics
- Git Basics
- Any Cheatsheet
- Deploy a ML Model using Flask on Heroku
- Web App using Flask
- Flask Heroku Github Integration
- Generic Flask API for sklearn Models
- Full Stack with Flask
- Flask mega-tutorial
- Deep Learning with Pytorch
- SQL Complete Tutorial
- SQL Notes for Professionals
- SQL Cheatsheet Slides
- Kaggle 😅
- Analytics Vidhya
- Numerical Intuition
- Google Machine Learning Crash Course
- Microsoft Forecasting Best Practices
- Solve NLP Problems
- Solve 90% NLP Problems like this
- NLTK Book ⚠
- Stanford NLP Course 👌
- Spacy Cheatsheet
- NLP Cheatsheet
- Google Resource Library
- Practicing Data Science Case Studies
- Daily Data Science Curriculum Schedule 🦥
- 4 Day Deep Learning Agenda 🍕
- Machine Learning Cheatsheet 📃
- Polo Club of Data Science to visualize AI 😎
- Data Engineering Interview Questions
- Data Engineering Basic Skills
Python
General/Programming
Job Search
Cracking TripleByte
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😅 That’s it for now! Will update if I find anything interesting!