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Fri frakt för medlemmar vid köp för minst 249:-
- Machine Learning Algorithms
- Basics of Python
- getting started with machine learning
- what is machine learning
- Installing machine libraries in your system
- Supervised Machine Learning for Discrete Class Label
- Machine learning methods
- K-Nearest Neighbors
- Decision Tree
- Support Vector Machine
- Naive Bayes Classification
- Logistic Regression
- Neural Network
- Regression Models
- Unsupervised Machine Learning
- Supervised Machine Learning for Continuous Class LabelUnderstanding and challenges
- Dimension Reduction
- Clustering Models
- Working with Text Data
- Representing Text Data as bags of words
- Stopwords
- Machine Learning Real World Applications
Machine Learning Real World Applications Representing Text Data as bags of words Stopwords Working with Text Data Understanding and challenges Dimension Reduction Clustering Models Unsupervised Machine Learning Regression Models Supervised Machine Learning for Continuous Class Label K-Nearest Neighbors Decision Tree Support Vector Machine Naive Bayes Classification Logistic Regression Neural Network Supervised Machine Learning for Discrete Class Label Machine learning methods What is machine learning Installing machine libraries in your system Getting Started with Machine learning
This book is not just a startup guide. This book will prove beneficial for years to come. The book has the latest codes and techniques so you can equip your skills according to the current market challenges. After all, the purpose is to land a nicely paid job in a globally recognized firm. This book will help you reach that goal!Most people can learn how to code but not just anyone can code smartly. This book is going to help you to think out of the box and take on problems with a completely different perspective. The tricks mentioned will make you invaluable to any software development firm.- Format: Pocket/Paperback
- ISBN: 9781801116015
- Språk: Engelska
- Antal sidor: 330
- Utgivningsdatum: 2020-10-18
- Förlag: Tony F. Charles