Welcome to the Data Science Roadmap! 🚀
This repository provides a structured and comprehensive guide for anyone interested in learning data science and Machine Learning, whether you're a beginner or looking to advance your skills.
- Intro to Statistics 🎥
- Statistics 1 (On YouTube) 🎥
- Arbic Course 🎥
Task: Solve this
Why Python? Show this
- Codemy.com 🎥
- FreeCodeCamp 🎥
- Kaggle 📕
Task: Solve this
Task: Solve this.
- Codezilla 🎥
- keepcoding 🎥
Task: Choose a category from Amazon, scrape relevant product data, and analyze insights such as pricing trends, ratings, and customer reviews.
After completing the Beginners and Intermediate stages, it's time to choose your path for advanced learning.
You can now proceed with one of the following tracks:
Alternatively, you can choose to study both tracks consecutively to gain comprehensive knowledge.
Each track includes courses and skills that will help you advance in your career.
- iti Course (matrial) and
- Sql Bi
to be continued.....
- Supervised Learning Course 🎥
- Unsupervised & Reinforcement Learning Course 🎥
- Advanced Learning Algorithms 🎥
- Book 📕
Learn how to deploy models and turn your solutions into production-ready applications.
- Neural Networks Course 🎥
- Improving Deep Neural Networks Course 🎥
- Convolutional Neural Networks Course 🎥
- Recurrent Neural Networks Course 🎥
- Refrence Book 📕
When to use? ease of use makes it perfect for research and prototyping custom models, e.g. building and experimenting with a GAN for image synthesis.
- Playlist 🎥
When to use? for deploying large-scale production models, e.g. training and deploying an image classification model
- Playlist 🎥
- This field concerned with the interactions between computers and human (natural) languages, in particular how to program computers to fruitfully process large amounts of natural language data.
to be continued.....