kaan
Kaan

Ai Data Science

#2

Data Science at the Command Line: Obtain, Scrub, Explore, and Model Data with Unix Power Tools

2021 • 1 Reader • 250 pages

#3

Veri Bilimi

56 The MIT Press Essential Knowledge

2020 • 1 Reader • 192 pages

#4

Çıplak İstatistik

15 Naked

2012 • 1 Reader • 400 pages

#5

Cover 0

31 Readers • 159 pages • 4

#6

Natural Language Processing With Python

8 Readers • 4

#7

Python Data Science Handbook

2016 • 6 Readers • 548 pages • 4

#8

The Art of Statistics

2019 • 65 Readers • 320 pages • 3.8

#9

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

2017 • 26 Readers • 819 pages • 5

#10

AI and Machine Learning for Coders

2020 • 392 pages

#11

Cover 6

1 Reader

#12

Practical Statistics for Data Scientists

2017 • 8 Readers • 395 pages

#13

Practical Natural Language Processing: A Comprehensive Guide to Building Real-world NLP systems

2020 • 375 pages

#14

Deep Learning for Coders with fastai and PyTorch: AI Applications Without a PhD

8 Readers

#15

Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps

4 Readers • 400 pages

#16

Storytelling with Data: A Data Visualization Guide for Business Professionals

2015 • 77 Readers • 252 pages • 4.3

#17

Pattern Recognition and Machine Learning

2016 • 24 Readers • 758 pages • 3.7

#18

Artificial intelligence

1994 • 46 Readers • 1,153 pages • 3.9

#19

Deep Learning for NLP and Speech Recognition

2019 • 1 Reader • 640 pages

#20

Practical Statistics for Data Scientists: 50 Essential Concepts

1 Reader • 363 pages

#21

Essential Math for Data Science: Take Control of Your Data with Fundamental Calculus, Linear Algebra, Probability, and Statistics

2020 • 1 Reader • 347 pages • 4

#22

Cover 8

2022 • 20 Readers • 426 pages • 4

#23

Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures

2019 • 390 pages

#24

Machine Learning Simplified: A Gentle Introduction to Supervised Learning

1 Reader • 109 pages

#25

Python for Data Analysis

2017 • 29 Readers • 676 pages • 4.3

#26

Süper Zekâ: Yapay Zekâ Uygulamaları, Tehlikeler ve Stratejiler

2014 • 1 Reader • 392 pages

#27

Probabilistic Machine Learning: An Introduction

11 Adaptive Computation and Machine Learning

2022 • 1 Reader • 858 pages

#28

Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications

2022 • 12 Readers • 368 pages • 3

#29

Seven Databases in Seven Weeks: A Guide to Modern Databases and the NoSQL Movement

2012 • 20 Readers • 3.5

#30

Machine Learning System Design Interview

2023 • 2 Readers • 294 pages

#31

An Introduction to Statistical Learning

2013 • 24 Readers • 426 pages • 3.7

#32

Cover 7

2008 • 1 Reader

#33

Probability

1986 • 1 Reader • 584 pages • 4

#34

Outlier Analysis

2016 • 466 pages

#35

Recommender Systems: The Textbook

2016 • 1 Reader • 498 pages

#36

Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition

2000 • 6 Readers • 577 pages

#37

Introduction to Information Retrieval

2008 • 482 pages

#38

Machine Learning: A Probabilistic Perspective

Planned book of 12 Adaptive Computation and Machine Learning

11 Readers

#39

Probabilistic Graphical Models: Principles and Techniques

11 Adaptive Computation and Machine Learning

2009 • 1,268 pages

#40

Foundations of Statistical Natural Language Processing

1999 • 4 Readers • 722 pages • 5

#41

Statistical Rethinking: A Bayesian Course with Examples in R and Stan

2015 • 11 Readers • 4.7

#42

Introduction to Machine Learning

11 Adaptive Computation and Machine Learning

2004 • 5 Readers • 584 pages

#43

AI-Powered Business Intelligence: Improving Forecasts and Decision Making with Machine Learning

2022 • 1 Reader • 350 pages

#44

The Self-Service Data Roadmap: Democratize Data and Reduce Time to Insight

2020 • 1 Reader • 350 pages

#45

Machine Learning Interviews

2023 • 1 Reader

#46

Deep Learning

11 Adaptive Computation and Machine Learning

2016 • 33 Readers • 800 pages • 4.6

#47

Deep Learning with Python

2017 • 14 Readers • 384 pages • 5

#48

Lean Analytics

2013 • 49 Readers • 440 pages • 3.8

#49

Cover 5

2019 • 1 Reader

#50

Machine Learning Engineering with Python: Manage the production life cycle of machine learning models using MLOps with practical examples

2021 • 1 Reader • 276 pages

#51

Hands-On Large Language Models

2024 • 2 Readers • 400 pages