"From Linear Regression to Deep Learning" - similar Books and Chapters

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Book	Author(s)	Year	Publisher
Tensorflow for Deep Learning: From Linear Regression to Reinforcement Learning	Bharath Ramsundar	2018	O'Reilly Media
Statistical Regression and Classification: From Linear Models to Machine Learning	Norman Matloff	2017	Routledge
Linear Regression	Jürgen Groß	2003	Springer Berlin Heidelberg
Linear Regression	David J. Olive	1st ed. 2017	Springer International Publishing
Deep Learning in Python Prerequisites: Master Data Science and Machine Learning with Linear Regression and Logistic Regression in Python (Machine Learning in Python)	LazyProgrammer
Introduction to Linear Regression Analysis	Elizabeth Peck, Geoffrey Vining, Douglas Montgomery	2012	Wiley series in probability and statistics
Introduction to linear regression analysis	Douglas C. Montgomery	1982	Wiley
Introduction to linear regression analysis /	Montgomery, Douglas C.; Peck, Elizabeth A.,; Vining, G. Geoffrey,	c2006.	Wiley-Interscience,
Introduction to linear regression analysis /	Montgomery, Douglas C.; Peck, Elizabeth A.,; Vining, G. Geoffrey,	[2001], ©2001.	Wiley,
Introduction to linear regression analysis /	Montgomery, Douglas C.,; Peck, Elizabeth A.,; Vining, G. Geoffrey,		Wiley & Sons, Incorporated, John
Introduction to linear regression analysis	Douglas C. Montgomery	1992	Wiley
Introduction to linear regression analysis	Douglas C. Montgomery	2012	Wiley
Applied linear regression /	Weisberg, Sanford,		Wiley & Sons, Incorporated, John
Applied linear regression	Sanford Weisberg	2005	Wiley-Interscience
Applied Linear Regression	Sanford Weisberg	2005	Wiley-Interscience
Applied linear regression	Sanford Weisberg	1980	Wiley
Linear regression analysis /	Seber, G. A. F.; Lee, Alan J.	[2003], ©2003.	John Wiley,
Linear regression diagnostics	Roy E. Welsch	1977	Alfred P. Sloan School of Management, Massachusetts Institute of Technology
Applied linear regression	Sanford Weisberg	1985	Wiley
Programming Machine Learning: From Coding to Deep Learning	Paolo Perrotta	2020	Pragmatic Bookshelf
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Chapter	Author(s)	Book	Book Authors	Year	Publisher
From Linear Regression to Deep Learning		Analytical Skills for AI and Data Science: Building Skills for an AI-Driven Enterprise	Daniel Vaughan	2020	O'Reilly Media
From Linear Regression to Deep Networks		Dive into Deep Learning	Aston Zhang, Zachary C. Lipton, Mu Li, and Alexander J. Smola	2021	d2l.ai
Supervised Learning—Linear Regression		Python Machine Learning	Wei-Meng Lee	2019	John Wiley & Sons
Chapter 5: From Simple Linear Regression to Multiple Linear Regression		Mastering Machine Learning with Scikit-Learn (Python)	Gavin Hackeling	2017	Packt Publishing
Sequence-to-Sequence Regression Using Deep Learning		MATLAB Deep Learning Toolbox™ User's Guide	The MathWorks, Inc.	2020	The MathWorks, Inc.
Moving on to logistic regression from linear regression		Learning predictive analytics with Python: gain practical insights into predictive modelling by implementing predictive analytics algorithms on public datasets with Python	Gulipalli, Pradeep; Kumar, Ashish	2016	Packt Publishing
Chapter 6: From Linear Regression to Logistic Regression		Mastering Machine Learning with Scikit-Learn (Python)	Gavin Hackeling	2017	Packt Publishing
Deep learning and regression analysis		Java for data science: examine the techniques and Java tools supporting the growing field of data science	Reese, Jennifer L.; Reese, Richard M	2017	Packt Publishing
Deep Reinforcement Learning: From Q-Learning to Deep Q-Learning	Fuxiao Tan; Pengfei Yan; Xinping Guan	Neural Information Processing: 24th International Conference, ICONIP 2017, Guangzhou, China, November 14–18, 2017, Proceedings, Part IV	Derong Liu; Shengli Xie; Yuanqing Li; Dongbin Zhao; El-Sayed M. El-Alfy	1st ed. 2017	Springer International Publishing
922 From Linear Regression to Regularized Regression to Support Vector Regression		Machine Learning With Python For Everyone	Mark E. Fenner	2020	Addison-Wesley Professional/Pearson education
Machine Learning and Linear Regression	Yasha Hasija; Rajkumar Chakraborty	Hands-On Data Science for Biologists Using Python	Yasha Hasija; Rajkumar Chakraborty	2021	Routledge
Learning Unit 13. Linear Regression		Core Statistical Concepts With Excel®: An Interactive Modular Approach	Gregory J. Privitera; Darryl J. Mayeaux	January 2019	SAGE Publications, Inc
Moving from machine learning to deep learning		Deep Learning for Dummies	Mueller, John Paul; Massaron, Luca	2019	For Dummies
Learning Theory: From Regression to Classification	Qiang Wu; Yiming Ying; Ding-Xuan Zhou	Topics in Multivariate Approximation and Interpolation	Kurt Jetter; Martin D. Buhmann; Werner Haussmann; Robert Schaback; Joachim Stöckler	2006	Elsevier
Deep Learning for Regression and Classification	Wing Kam Liu; Zhengtao Gan; Mark Fleming	Mechanistic Data Science for STEM Education and Applications	Wing Kam Liu; Zhengtao Gan; Mark Fleming	1st ed. 2021	Springer International Publishing
Deep Active Learning for Image Regression	Hiranmayi Ranganathan; Hemanth Venkateswara; Shayok Chakraborty; Sethuraman Panchanathan	Deep Learning Applications	M. Arif Wani; Mehmed Kantardzic; Moamar Sayed-Mouchaweh	1st ed. 2020	Springer Nature Singapore
Introduction to Linear Regression	Fred Pyrczak	Success at Statistics: A Worktext with Humor	Fred Pyrczak	2016	Routledge
Introduction to Linear Regression		2022 CFA Program Curriculum Level I Quantitative Methods	CFA Institute	2021	Wiley
Reduction to linear regression		TensorFlow Machine Learning Cookbook: Over 60 Recipes to Build Intelligent Machine Learning Systems with the Power of Python, 2nd Edition	Nick McClure	2018	Packt Publishing - ebooks Account
Introduction to Linear Regression		The Python Workshop: Learn to code in Python and kickstart your career in software development or data science	Andrew Bird, Dr Lau Cher Han, Mario Corchero Jimenez, Graham Lee, Corey Wade	2019	Packt Publishing
Chapter	Author(s)	Book	Book Authors	Year	Publisher

Showing 1 to 20 of 100 entries