“If you only read the books that everyone else is reading, you can only think what everyone else is thinking.”

Every person has their own way of learning. What helped me break into data science was books. There is nothing like opening your mind to a world of knowledge condensed into a few hundred pages. There is a magic and allure to books that I have never found in any other medium of learning.

There are hundreds of books out there about data science. How do you choose where to start? Which books are ideal for learning a certain technique or domain? While there’s no one-shoe-fits-all answer to this, I have done my best to cut down the list to these 27 books we’ll see shortly.

I have divided the books into different domains to make things easier for you:

1. Books on Statistics
2. Books on Probability
3. Books on Machine Learning
4. Books on Deep Learning
5. Books on Natural Language Processing (NLP)
6. Books on Computer Vision
7. Books on Artificial Intelligence
8. Books on Tools/Languages
- Python
- R

Link : https://bit.ly/2IOPV8T

#python #books #artificialintelligence #datascience
#machinelearning #statistics #datascientist #deeplearning

✴️ @AI_Python_EN