Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits
portes grátis
Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits
A practical guide to implementing supervised and unsupervised machine learning algorithms in Python
Amr, Tarek
Packt Publishing Limited
07/2020
384
Mole
Inglês
9781838826048
15 a 20 dias
Descrição não disponível.
Table of Contents
Introduction to Machine Learning & Scikit-Learn
Making Decisions with Trees
Making decisions with linear equations
Preparing Your Data
Image processing with nearest neighbors
Text Classification - Not all data exists in tables
Neural Networks - Here comes the Deep Learning
Ensembles - When one model is not enough
The Y is as important as the X
Imbalanced Learn - Not even 1% win the lottery
Clustering - Grouping data when no correct answers are provided
Anomaly Detection - Finding Outliers in Data
Recommender System - Learning about users' taste from their previous interactions
Introduction to Machine Learning & Scikit-Learn
Making Decisions with Trees
Making decisions with linear equations
Preparing Your Data
Image processing with nearest neighbors
Text Classification - Not all data exists in tables
Neural Networks - Here comes the Deep Learning
Ensembles - When one model is not enough
The Y is as important as the X
Imbalanced Learn - Not even 1% win the lottery
Clustering - Grouping data when no correct answers are provided
Anomaly Detection - Finding Outliers in Data
Recommender System - Learning about users' taste from their previous interactions
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Machine learning;machine learning algorithms;Neural networks;Scikit-Learn;supervised learning;unsupervised learning
Table of Contents
Introduction to Machine Learning & Scikit-Learn
Making Decisions with Trees
Making decisions with linear equations
Preparing Your Data
Image processing with nearest neighbors
Text Classification - Not all data exists in tables
Neural Networks - Here comes the Deep Learning
Ensembles - When one model is not enough
The Y is as important as the X
Imbalanced Learn - Not even 1% win the lottery
Clustering - Grouping data when no correct answers are provided
Anomaly Detection - Finding Outliers in Data
Recommender System - Learning about users' taste from their previous interactions
Introduction to Machine Learning & Scikit-Learn
Making Decisions with Trees
Making decisions with linear equations
Preparing Your Data
Image processing with nearest neighbors
Text Classification - Not all data exists in tables
Neural Networks - Here comes the Deep Learning
Ensembles - When one model is not enough
The Y is as important as the X
Imbalanced Learn - Not even 1% win the lottery
Clustering - Grouping data when no correct answers are provided
Anomaly Detection - Finding Outliers in Data
Recommender System - Learning about users' taste from their previous interactions
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
