My Data Science Roadmap
Why this?
I want to track the progress of my studies in this broad area. I do not intend to list a huge number of resources or courses, just the ones that I have completed so far and the following ones that are on my mind for a next step (in a short/medium or even long term). Anyway, valuable resources that may be part of my plan in the future.
1. Courses
This section is to list the courses taken and those that will be done in the future.
2. Books
This is a selection of books for Data Science and related disciplines from which I have good references. The books are listed in descending order of publication date.
| Title | Author | Publisher | Release Date | |
|---|---|---|---|---|
| ◻️ | Machine Learning with Python | Chris Albon | O'Reilly Media | March 2018 |
| ◻️ | Jupyter for Data Science | Dan Toomey | O'Reilly Media | October 2017 |
| ◻️ | Mastering Machine Learning with scikit-learn | Gavin Hackeling | Packt | October 2014 |
| ◻️ | Introduction to Machine Learning with Python | David James | AI Sciences | Aug 2018 |
| ◻️ | Hands-On Machine Learning with Scikit-Learn and Tensorflow | Aurélien Géron | O'Reilly Media | March 2017 |
3. References
- Pandas Documentation
- Scikit-Learn Documentation
- TensorFlow
- Keras
- Numpy and Scipy Documentation
- Amazing Cheats Sheet DataCamp
4. Contact
Linkedin: https://www.linkedin.com/in/joaopaulolndev/
Email: joaopaulolndev@gmail.com