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Machine Learning with scikit-learn Quick Start Guide

learning environment with scikit-learn. To put scikit-learn to use, you will learn how to implement various supervised and unsupervised machine;

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Hands-on Scikit-Learn for Machine Learning Applications

Aspiring data science professionals can learn the Scikit-Learn library along with the fundamentals of machine learning with this book. The;

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Mastering Machine Learning with scikit-learn -

Use scikit-learn to apply machine learning to real-world problems About This Book * Master popular machine learning models including;

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scikit-learn Cookbook -

variety of machine learning tasks effortlessly by leveraging the power of scikit-learn * Perform supervised and unsupervised learning with ease;

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Machine Learning with Scikit-Learn and TensorFlow

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Machine Learning Fundamentals

With the flexibility and features of scikit-learn and Python, build machine learning algorithms that optimize the programming process and;

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Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits

machine learning problems Key Features Delve into machine learning with this comprehensive guide to scikit-learn and scientific Python Master the;

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Learning scikit-learn

experience with machine-learning algorithms is required.;

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Hands-On Machine Learning with Scikit-Learn and TensorFlow

scikit-learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision;

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Machine Learning mit Python und Keras, TensorFlow 2 und Scikit-learn

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Hands-on Machine Learning with Python

unsupervised learning Examine convolutional neural networks and Recurrent neural networks Get acquainted with scikit-learn and PyTorch Predict;

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Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow

Scikit-Learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision;

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Hands-on Machine Learning with Python

visualizations. The second section covers machine learning basics and Scikit-learn library. It also explains supervised learning, unsupervised learning;

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Mastering Machine Learning Algorithms

with popular machine learning algorithms. You will be introduced to the most widely used algorithms in supervised, unsupervised, and semi;

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Mastering Machine Learning with Python in Six Steps

in Scikit-learn are covered as well. You'll also learn commonly used model diagnostic and tuning techniques. These include optimal probability;

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Mastering Machine Learning with Python in Six Steps

enable you to try out these examples and extend them to your advantage. What You'll Learn Understand machine learning development and;

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Introduction to Machine Learning with Python

the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and;

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Python Machine Learning

latest additions to scikit-learn. It's also expanded to cover cutting-edge reinforcement learning techniques based on deep learning, as well as;

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Python Feature Engineering Cookbook

Extract accurate information from data to train and improve machine learning models using NumPy, SciPy, pandas, and scikit-learn libraries;

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Mastering Predictive Analytics with scikit-learn and TensorFlow

can be used in the field of data science. Mastering Predictive Analytics with scikit-learn and TensorFlow covers various implementations;

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Mastering Machine Learning Algorithms

, and train supervised and semi-supervised models by making use of Python-based libraries such as scikit-learn. You will also discover practical;

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Machine Learning for OpenCV 4

scikit-learn Get up to speed with Intel OpenVINO and its integration with OpenCV 4 Implement high-performance machine learning models with;

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Data Science Projects with Python

Gain hands-on experience of Python programming with industry-standard machine learning techniques using pandas, scikit-learn, and XGBoost;

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Beginning Anomaly Detection Using Python-Based Deep Learning

is important in today's world Become familiar with statistical and traditional machine learning approaches to anomaly detection using Scikit-Learn;

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Python Machine Learning -

, Python Machine Learning Second Edition now includes the popular TensorFlow deep learning library. The scikit-learn code has also been fully;

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Machine Learning Pocket Reference Working with Structured Data in Python

learning process and walks you through classification with structured data. You'll also learn methods for clustering, predicting a continuous value;

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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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