Produkt
Klappentext"Please note that the official seller in India is Pothi. Other sellers are selling printouts/photocopies for cheaper prices"
This is not a traditional book.
>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
>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
This is not a traditional book.
>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
>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
Details
ISBN/GTIN978-82-692115-0-4
ProduktartTaschenbuch
EinbandartKartoniert, Paperback
Verlag
Erscheinungsjahr2020
Erscheinungsdatum30.06.2020
Seiten302 Seiten
SpracheEnglisch
MasseBreite 154 mm, Höhe 231 mm, Dicke 20 mm
Gewicht426 g
Artikel-Nr.60987791
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