Author: ajit jaokar
In this post, I explain
- How you can participate further in the free book series which we are launching based on the early experiences and
- Useful resources we recommend based on our experience for learning coding for Data Science (using Python – tensorflow and keras)
To provide some context, I posted about the idea of learning coding for machine learning / deep learning in a weekend We have had considerable success with this – and now we are planning the next stage.
To participate in this book series and to get the free books – please join this group
AI deeplearning machinelearning coding in a week
The first book in this series is
Coding in a weekend – Classification and Regression launched in Apr 2019
Each book will have
- An outline and context of the problem
- Code based on a single program
- Step by step explanation based on our experience in teaching this code i.e. the deliberate practise step which I explained in learning coding for machine learning / deep learning in a weekend
- Community i.e. the group where you can ask questions
forthcoming books in this series are (note the group will remain the same i.e. AI deeplearning machinelearning coding in a week)
- a) Deep learning
- b) Introduction to Machine Learning coding for the Cloud – Azure
- d) Introduction to Machine Learning coding for the Cloud – Google Cloud Platform
Created and managed by Ajit Jaokar, Dan Howarth, Ayse Mutlu – London UK. we welcome other community moderators. The books are free but exclusive to Data Science Central
Finally, from our trials, here are five great free resources we recommend
1) Python Data Science Handbook by Jake VanderPlas
3) Python crash course by Eric Matthes
4) Python crash course by Eric Matthes cheat sheets
I highly recommend Chris Albon book – however the book itself is not free. But the site above provides code in lots of granular detail for the book and we found the code very useful (and we bought the book)
Don’t forget to join the group for the free books
AI deeplearning machinelearning coding in a week
Image source https://outreach.wikimedia.org/wiki/Bookshelf/Wikipedia