3Blue1Brown
3Blue1Brown is a captivating YouTube channel that brings complex mathematical concepts to life through stunning animations and clear explanations. Created by Grant Sanderson, this channel is a must-watch for anyone interested in understanding the beauty and depth of mathematics, from linear algebra to calculus and beyond.
StatQuest
StatQuest, hosted by Josh Starmer, is an invaluable YouTube channel that demystifies complex statistical concepts and machine learning algorithms with clarity and humor. With its catchy jingles and straightforward explanations, StatQuest is the go-to resource for students, data scientists, and anyone looking to enhance their understanding of statistics and data analysis.
Mathemaniac
Not quite a data science channel, but too good to be missed. After all, the DS subject is built on math per se. The channel offers fresh perspectives on traditional mathematical topics through innovative animations and unique explanations. It explores novel concepts not typically found in standard math curricula, making it an excellent resource for students and enthusiasts looking to deepen their understanding and appreciation of mathematics.
538
FiveThirtyEight, founded by renowned statistician Nate Silver, is a YouTube channel offering insightful analysis of politics, sports, and science through data and statistics. With its engaging content and rigorous approach to data interpretation, FiveThirtyEight is a must-watch for anyone interested in understanding how numbers shape our world and influence decision-making in various fields.
Sentdex
A highly popular YouTube channel that offers comprehensive tutorials on Python programming, machine learning, and artificial intelligence. With its practical, hands-on approach and clear explanations, Sentdex is an excellent resource for beginners and intermediate programmers looking to expand their skills in data science and AI applications.
Deep Learning Specialization
The Deep Learning Specialization on Coursera, created by Andrew Ng, is a comprehensive five-course series that provides a solid foundation in deep learning concepts and techniques. This program is highly recommended for anyone looking to master the fundamentals of neural networks, convolutional networks, and sequence models, offering hands-on projects and practical skills that can be applied to real-world AI challenges.
Introduction to Deep Learning
MIT’s Introduction to Deep Learning is a comprehensive and accessible course that offers a solid foundation in deep learning methods and their applications across various fields. This program, available in-person and online, is highly recommended for students and professionals seeking practical experience building neural networks and understanding cutting-edge topics like large language models and generative AI. With its hands-on approach and project-based learning, this course is an excellent starting point for anyone looking to dive into the world of deep learning, regardless of their background in computer science.
Check out my workshop about object-oriented programming and tableau usage logic.
Check out books that I find valuable for learning and personal growth.
The Equation of Knowledge:
From Bayes’ Rule to a Unified Philosophy of Science
ISBN-13 978-0367428143
This book provides a thoughtful exploration of how Bayes’ theorem underpins scientific inquiry and decision-making. The book bridges complex statistical concepts with philosophical ideas, offering a unique perspective on acquiring and interpreting knowledge. It’s a must-read for anyone interested in the deeper connections between mathematics, reasoning, and the philosophy of science.
Python Machine Learning
ISBN-13 978-1789955750
This book is a comprehensive guide to mastering machine learning using Python. It covers key concepts, algorithms, and practical implementations, making it ideal for both beginners and experienced practitioners. With clear explanations and hands-on examples, this book is a valuable resource for anyone looking to enhance their understanding of machine learning techniques in Python.
R Graphics Cookbook: Practical Recipes for Visualizing Data
ISBN-13 978-1491978603
This book is an excellent resource for anyone looking to create effective and visually appealing data visualizations using R. The book offers easy-to-follow, practical recipes for a wide range of graphics, making it suitable for both beginners and experienced users. With its clear instructions and diverse examples, it’s an invaluable guide for mastering data visualization in R.
Fundamentals of Data Visualization:
A Primer on Making Informative and Compelling Figures
ISBN-13 978-1492031086
This book is an essential guide for anyone looking to improve their data visualization skills. The book provides practical advice on creating visually engaging and informative figures that effectively communicate data insights. With a focus on aesthetics and clarity, it’s perfect for beginners and experienced professionals who want to make their visualizations more impactful.
Visualization Analysis and Design
ISBN-13 978-1466508910
An authoritative textbook written by leading scientists in data visualization. While it may be more suited for future visualization researchers covering topics like design studies for interactive visualization software, it stands out for its comprehensive coverage of science and practice. It’s highly recommended for anyone looking to gain deep insights into the principles and methodologies of effective data visualization.
Oracle Database 12c SQL
ISBN-13 978-0071799355
An excellent resource for learning and mastering SQL in Oracle Database 12c. It covers essential SQL concepts and practical applications, making it ideal for beginners and experienced users looking to enhance their database management skills. With clear explanations and real-world examples, this book is a valuable tool for anyone working with Oracle databases.
Neural Networks and Deep Learning
by Michael Nielsen
Online resources, no physical edition. Cover for display purposes only.
This book is an excellent introduction to the core concepts of neural networks, offering clear explanations and hands-on examples. It guides readers through essential topics like backpropagation and gradient descent, making complex ideas accessible to those new to deep learning. It’s an ideal resource for anyone looking to build a solid foundation in neural networks while gaining practical experience with Python.
Business Intelligence Guidebook: From Data Integration to Analytics
ISBN-13 978-0124114616
It provides a comprehensive guide to the business intelligence process, from data integration to advanced analytics. The book offers practical insights into building effective BI systems, making it a valuable resource for business and technical professionals. Its thorough coverage of best practices and real-world applications makes it an essential tool for anyone looking to leverage data for better decision-making.
Mining of Massive Datasets
ISBN-13 978-1107077232
A comprehensive resource for understanding the techniques and algorithms needed to analyze large-scale data. Written by Stanford professors, it covers key topics such as distributed data processing with MapReduce, machine learning, graph analytics, and recommendation systems. With its practical approach and clear explanations, this book is ideal for students and professionals looking to gain deep insights into the challenges and solutions of big data analysis.
Only available in Simplified Chinese for now.