Shikhar Upadhyay Shikharishere

1. The C Programming Language - Brian Kernighan and Dennis Ritchie
2. Python Crash Course - Erich Matthes
3. Djnago For Beginners - William Vincent
4. Computer Networking A Top Down Approach - Jim Kurose and Keith Ross
5. Computer Science Distilled - Wladston Ferreira Filho

For ML Interviews : https://github.com/khangich/machine-learning-interview
For ML in Production : https://github.com/EthicalML/awesome-production-machine-learning
For ML with different languages : https://github.com/josephmisiti/awesome-machine-learning/tree/master
For ML Videos, Courses etc. : https://github.com/ujjwalkarn/Machine-Learning-Tutorials
For Best ML tools created with Python : https://github.com/ml-tooling/best-of-ml-python
For ML project Ideas : https://github.com/lukas/ml-class
https://github.com/rhiever/Data-Analysis-and-Machine-Learning-Projects

Ok. I'm going to list off some ideas for projects. You will have to determine if any particular idea is good enough to include in a portfolio. These aren't creative ideas. They likely already exist. Some are way too advanced while others are simplistic.

I will recommend to post any project you make to github and make a github project page for it. Explain in as much detail as possible how you made it, how it can be improved etc. Document it.

If you pick an advanced idea, setup a development roadmap and follow it. This will show some project management skills.

Another piece of advice for those who are design challenged. Use different front end frameworks and use different themes for those frameworks to provide appealing designs without looking like yet another bootstrap site.