Bộ sách luyện thi ETS 2023 LC&RC
199,000₫
299,000₫
Sách keo gáy, bìa mềm
This is not a traditional book.
The
book has a lot of code. If you don't like the code first approach do
not buy this book. Making code available on Github is not an option.
This
book is for people who have some theoretical knowledge of machine
learning and deep learning and want to dive into applied machine
learning. The book doesn't explain the algorithms but is more oriented
towards how and what should you use to solve machine learning and deep
learning problems. The book is not for you if you are looking for pure
basics. The book is for you if you are looking for guidance on
approaching machine learning problems. The book is best enjoyed with a
cup of coffee and a laptop/workstation where you can code along.
Table of contents:
- Setting up your working environment
- Supervised vs unsupervised learning
- Cross-validation
- Evaluation metrics
- Arranging machine learning projects
- Approaching categorical variables
- Feature engineering
- Feature selection
- Hyperparameter optimization
- Approaching image classification & segmentation
- Approaching text classification/regression
- Approaching ensembling and stacking
- Approaching reproducible code & model serving
There are no sub-headings. Important terms are written in bold.
I
will be answering all your queries related to the book and will be
making YouTube tutorials to cover what has not been discussed in the
book. To ask questions/doubts, please create an issue on github repo:
https://github.com/abhishekkrthakur/approachingalmost
And Subscribe to my youtube channel: https://bit.ly/abhitubesub
Thể loại:Computers - Artificial Intelligence (AI)
Năm:2020
Ngôn ngữ:english
Trang:300
