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There was a problem previewing this document. Machine Learning blogger.com - Free download Ebook, Handbook, Textbook, User Guide PDF files on the internet quickly and easily. Oreilly Learning Python 5th blogger.com - Free download Ebook, Handbook, Textbook, User Guide PDF files on the internet quickly and easily.
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Explore a preview version of Introduction to Machine Learning with Python right now. Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions.
With all the data available today, machine learning applications are limited only by your imagination. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book. Skip to main content. Start your free trial. Book Description Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams.
Show and hide more. Table of Contents Product Information. Introduction 1. Why Machine Learning? Problems Machine Learning Can Solve 1, learning python oreilly pdf free download. Why Python? Installing scikit-learn 1. Essential Libraries and Tools 1.
Jupyter Notebook 1. NumPy 1. SciPy 1. Python 2 Versus Python 3 1. Versions Used in this Book 1. Meet the Data 1. Measuring Success: Training and Testing Data 1. Making Predictions 1. Evaluating the Model 1. Summary and Outlook 2. Supervised Learning 2. Classification and Regression 2. Generalization, Overfitting, and Underfitting 2. Relation of Model Complexity to Dataset Size 2. Supervised Machine Learning Learning python oreilly pdf free download 2. Some Sample Datasets 2.
Linear Models 2. Naive Bayes Classifiers 2. Decision Trees 2. Ensembles of Decision Trees learning python oreilly pdf free download. Kernelized Support Vector Machines 2. Neural Networks Deep Learning 2. Uncertainty Estimates from Classifiers 2. The Decision Function 2, learning python oreilly pdf free download. Predicting Probabilities 2. Uncertainty in Multiclass Classification 2.
Summary and Outlook 3. Unsupervised Learning and Preprocessing 3. Types of Unsupervised Learning 3. Challenges in Unsupervised Learning 3.
Preprocessing and Scaling 3. Different Kinds of Preprocessing 3. Applying Data Transformations 3. The Effect of Preprocessing on Supervised Learning 3. Manifold Learning with t-SNE 3. Clustering 3. Agglomerative Clustering 3. Comparing and Evaluating Clustering Algorithms 3. Summary of Clustering Methods 3. Summary and Outlook 4. Representing Data and Learning python oreilly pdf free download Features 4. Categorical Variables 4. One-Hot-Encoding Dummy Variables 4.
Numbers Can Encode Categoricals 4. Binning, Discretization, Linear Models, and Trees 4. Interactions and Polynomials 4. Univariate Nonlinear Transformations 4. Automatic Feature Selection 4. Univariate Statistics 4.
Model-Based Feature Selection 4. Iterative Feature Selection 4. Utilizing Expert Knowledge 4. Summary and Outlook 5. Model Evaluation and Improvement 5. Cross-Validation 5. Cross-Validation in scikit-learn 5. Benefits of Cross-Validation 5. Grid Search 5. Simple Grid Search 5. Grid Search with Cross-Validation 5. Evaluation Metrics and Scoring 5. Keep the End Goal in Mind 5. Metrics for Binary Classification 5. Metrics for Multiclass Classification 5.
Regression Metrics 5. Using Evaluation Metrics in Model Selection 5. Summary and Outlook 6. Algorithm Chains and Pipelines 6. Parameter Selection with Preprocessing 6. Building Pipelines 6. Using Pipelines in Grid Searches 6. The General Pipeline Interface 6. Accessing Step Attributes 6. Avoiding Redundant Computation 6.
Summary and Outlook 7. Working with Text Data 7. Types of Data Represented as Strings 7. Representing Text Data as a Bag of Words 7. Applying Bag-of-Words to a Toy Dataset 7, learning python oreilly pdf free download. Bag-of-Words for Movie Reviews 7. Stopwords 7. Rescaling the Data with tf—idf 7. Investigating Model Coefficients 7.
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Machine Learning blogger.com - Free download Ebook, Handbook, Textbook, User Guide PDF files on the internet quickly and easily. There was a problem previewing this document. Learning Python, 5th Edition Powerful Object-Oriented Programming. By Mark Lutz. Publisher: O'Reilly Media. Release Date: June Pages: Read on O'Reilly Online Learning with a day trial Start your free trial now Buy on Amazon.
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