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Supervised Machine Learning for Text Analysis in R

workflows for predictive modeling using text as features Compare traditional machine learning methods and deep learning methods for text data;

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Supervised Machine Learning for Text Analysis in R

workflows for predictive modeling using text as features Compare traditional machine learning methods and deep learning methods for text data;

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Machine Learning for Knowledge Discovery with R

Machine Learning for Knowledge Discovery with R contains methodologies and examples for statistical modelling, inference, and prediction;

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Applied Machine Learning for Smart Data Analysis

unsupervised and semi-supervised machine learning techniques with study of semantic analysis and thorough analysis of reviews. Divided into sections;

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Machine Learning Foundations

This book provides conceptual understanding of machine learning algorithms though supervised, unsupervised, and advanced learning;

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Supervised Machine Learning

AI framework intended to solve a problem of bias-variance tradeoff for supervised learning methods in real-life applications. It comprises;

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Applied Supervised Learning with R

Learning with R helps you cover the complete process of employing R to develop applications using supervised machine learning algorithms for your;

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Machine Learning and Data Science

techniques required to excel with statistical learning methods in the areas of data access, data munging, exploratory data analysis, supervised;

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Machine Learning with PySpark

supervised machine learning models such as linear regression, logistic regression, decision trees, and random forest. You'll also see unsupervised;

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Mastering Machine Learning Algorithms

of regression analysis, time series analysis, deep learning models, and cutting-edge applications Book DescriptionMastering Machine Learning Algorithms;

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Supervised Machine Learning

AI framework intended to solve a problem of bias-variance tradeoff for supervised learning methods in real-life applications. The AI;

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Supervised Machine Learning

AI framework intended to solve a problem of bias-variance tradeoff for supervised learning methods in real-life applications. The AI;

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Behavior Analysis with Machine Learning Using R

Behavior Analysis with Machine Learning Using R introduces machine learning and deep learning concepts and algorithms applied to a diverse;

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Mastering Machine Learning with R -

insights into the application of machine learning tools in the industry * Manipulate data in R efficiently to prepare it for analysis * Master;

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TensorFlow 2.0 Quick Start Guide

your own models for effective prediction, using high-level Keras API Perform supervised and unsupervised machine learning and learn advanced;

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Welding and Cutting Case Studies with Supervised Machine Learning

learning. Subsequently, it discusses supervised learning, highlighting Python libraries such as NumPy, Pandas and Scikit Learn programming. It also;

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Welding and Cutting Case Studies with Supervised Machine Learning

learning. Subsequently, it discusses supervised learning, highlighting Python libraries such as NumPy, Pandas and Scikit Learn programming. It also;

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Introduction to Machine Learning with R

learning algorithms for supervised and unsupervised cases Examine statistical concepts for designing data for use in models Dive into linear;

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Machine Learning and Data Science Blueprints for Finance From Building Trading Strategies to RoboAdvisors Using Python

over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP). Ideal for;

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Machine Learning Fundamentals

Understand the difference between supervised and unsupervised models Learn the usage of machine learning through real-world examples Book;

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Hands-on Machine Learning with Python

Here is the perfect comprehensive guide for readers with basic to intermediate level knowledge of machine learning and deep learning. It;

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Hands-on Machine Learning with Python

Here is the perfect comprehensive guide for readers with basic to intermediate level knowledge of machine learning and deep learning. It;

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Machine Learning in Complex Networks

in details some specific techniques based on complex networks for supervised, non-supervised, and semi-supervised learning. Particularly, a;

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Machine Learning in Complex Networks

in details some specific techniques based on complex networks for supervised, non-supervised, and semi-supervised learning. Particularly, a;

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Machine Learning Algorithms

wants to advance in the field of predictive analytics and machine learning. Familiarity with R and Python will be an added advantage for getting;

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Machine Learning with scikit-learn Quick Start Guide

DescriptionScikit-learn is a robust machine learning library for the Python programming language. It provides a set of supervised and unsupervised learning;

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Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction

> Features various supervised machine learning based regression models Offers global case studies for turbine wind farm layouts

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