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Windows 11: 2021 Complete New OS User Guide. 33 Best Tips and Tricks to Master your PC
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4.45 avg rating — 40 ratings
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Introduction to Algorithms
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An Introduction to Statistical Learning: with Applications in R
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Pattern Recognition and Machine Learning
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The Algorithm Design Manual
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Machine Learning: A Probabilistic Perspective
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Machine Learning with Neural Networks: An In-depth Visual Introduction with Python: Make Your Own Neural Network in Python: A Simple Guide on Machine Learning with Neural Networks.
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Bayesian Data Analysis
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Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction
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Machine Learning: An Introduction Math Guide for Beginners to Understand Data Science Through the Business Applications
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Machine Learning: 4 Books in 1: A Complete Overview for Beginners to Master the Basics of Python Programming and Understand How to Build Artificial Intelligence Through Data Science
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Probabilistic Graphical Models: Principles and Techniques
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Machine Learning in Action
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Neural Networks for Pattern Recognition (Advanced Texts in Econometrics (Paperback))
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Python Machine Learning
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The Math of Neural Networks
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Machine Learning Mathematics: Study Deep Learning Through Data Science. How to Build Artificial Intelligence Through Concepts of Statistics, Algorithms, Analysis and Data Mining
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Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology
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Information Theory, Inference, and Learning Algorithms
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Foundations of Statistical Natural Language Processing
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Interactive Data Visualization for the Web: An Introduction to Designing with D3
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Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
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Computer Age Statistical Inference: Algorithms, Evidence, and Data Science (Institute of Mathematical Statistics Monographs, Series Number 5)
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Introduction to Computation and Programming Using Python
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Mathematica Data Analysis
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Artificial Intelligence: A 60 Minute Guide
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Taxonomy of the most commonly used Machine Learning Algorithms
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Machine Learning for Imbalanced Data: Tackle imbalanced datasets using machine learning and deep learning techniques
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Multiple Correspondence Analysis (Quantitative Applications in the Social Sciences Book 163)
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Scratch Programming Lab 01: Detailed step by step guide for middle school students.
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Decision Trees and Random Forests: A Visual Introduction For Beginners: A Simple Guide to Machine Learning with Decision Trees
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Artificial Intelligence and Machine Learning for Business: A No-Nonsense Guide to Data Driven Technologies
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Cognitive Biases: A Brief Overview of Over 160 Cognitive Biases + Bonus Chapter: Algorithmic Bias
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Problem Solving With Algorithms And Data Structures Using Python
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Data Analysis Using Regression and Multilevel/Hierarchical Models
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Causality: Models, Reasoning, and Inference
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Designing Social Inquiry: Scientific Inference in Qualitative Research
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The Visual Display of Quantitative Information
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Agile Data Science: Building Data Analytics Applications with Hadoop
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Pattern Classification
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