Atomic Habits: An Easy & Proven Way to Build Good Habits & Break Bad Ones
This book is not about data science or machine learning, but I think anyone interested in building a productive life would love to read it, understand it, and start applying the techniques described in the book to real life.
I have read and listened to it in my native language and I am going to read it again in English. I believe that such books should be re-read once a year or two to refresh the information in memory.
10 Things This Book Will Teach You
Learn how to…
- Build a system for getting 1% better every day.
- Break your bad habits and stick to good ones.
- Avoid the common mistakes most people make when changing habits.
- Overcome a lack of motivation and willpower.
- Develop a stronger identity and believe in yourself.
- Make time for new habits (even when life gets crazy).
- Design your environment to make success easier.
- Make tiny, easy changes that deliver big results.
- Get back on track when you get off course.
- And most importantly, how to put these ideas into practice in real life.
…and much more.
I also recommend to sign up for the 3-2-1 Newsletter from the author of the book using the link in the comments section:
"The 3-2-1 Newsletter is one of the most popular newsletters in the world. Every Thursday, the latest issue is sent to over 2,000,000 people. Each message includes 3 short ideas from me, 2 quotes from others, and 1 question for you to ponder"
#armbooks #armknowledgesharing #book #habits #selfhelp #motivation
This book is not about data science or machine learning, but I think anyone interested in building a productive life would love to read it, understand it, and start applying the techniques described in the book to real life.
I have read and listened to it in my native language and I am going to read it again in English. I believe that such books should be re-read once a year or two to refresh the information in memory.
10 Things This Book Will Teach You
Learn how to…
- Build a system for getting 1% better every day.
- Break your bad habits and stick to good ones.
- Avoid the common mistakes most people make when changing habits.
- Overcome a lack of motivation and willpower.
- Develop a stronger identity and believe in yourself.
- Make time for new habits (even when life gets crazy).
- Design your environment to make success easier.
- Make tiny, easy changes that deliver big results.
- Get back on track when you get off course.
- And most importantly, how to put these ideas into practice in real life.
…and much more.
I also recommend to sign up for the 3-2-1 Newsletter from the author of the book using the link in the comments section:
"The 3-2-1 Newsletter is one of the most popular newsletters in the world. Every Thursday, the latest issue is sent to over 2,000,000 people. Each message includes 3 short ideas from me, 2 quotes from others, and 1 question for you to ponder"
#armbooks #armknowledgesharing #book #habits #selfhelp #motivation
James Clear
Atomic Habits: An Easy & Proven Way to Build Good Habits & Break Bad Ones
Packed with evidence-based strategies, Atomic Habits will teach you how to make small changes that will transform your habits and deliver amazing results.
Machine Learning Simplified:
A gentle introduction to supervised learning
The underlying goal of "Machine Learning Simplified" is to develop strong intuition for ML inside you. We would use simple intuitive examples to explain complex concepts, algorithms or methods, as well as democratize all mathematics behind machine learning.
After reading this book, you would understand everything that comes into the scope of Supervised ML, and would be able to not only understand nitty-gritty details of mathematics behind the scene, but also explain to anyone how things work on a high level.
The book is free, but you can purchase EPUB version through Amazon or show your appreciation to the author and purchase PDF through Leanpub.
Table of contents:
I. FUNDAMENTALS OF SUPERVISED LEARNING
Chapter 1. Introduction
Chapter 2. Overview of Supervised Learning
Chapter 3. Model Learning
Chapter 4. Basis Expansion & Regularization
Chapter 5. Model Selection
Chapter 6. Feature Selection
Chapter 7. Data Preparation
II. ADVANCED SUPERVISED LEARNING ALGORITHMS (WIP)
Chapter 1. Regression Models
Chapter 2. Logit Models
Chapter 3. Bayesian Models
Chapter 4. Maximum Margin Models
Chapter 5. Tree-Based Models
Chapter 6. Ensemble Models
Chapter 7. Algorithms Selection
Chapter 8. Hyperparameter Tuning
Chapter 9. Evaluation Metrics
Read for free: https://themlsbook.com/read
Buy on Amazon: https://www.amazon.com/dp/B0B216KMM4/qid=1653304321
Buy on LeanPub: https://leanpub.com/themlsbook
Repository: https://code.themlsbook.com/
Navigational hashtags: #armknowledgesharing #armbooks
General hashtags: #machinelearning #ml #algorithms #learning #book
@data_science_weekly
A gentle introduction to supervised learning
The underlying goal of "Machine Learning Simplified" is to develop strong intuition for ML inside you. We would use simple intuitive examples to explain complex concepts, algorithms or methods, as well as democratize all mathematics behind machine learning.
After reading this book, you would understand everything that comes into the scope of Supervised ML, and would be able to not only understand nitty-gritty details of mathematics behind the scene, but also explain to anyone how things work on a high level.
The book is free, but you can purchase EPUB version through Amazon or show your appreciation to the author and purchase PDF through Leanpub.
Table of contents:
I. FUNDAMENTALS OF SUPERVISED LEARNING
Chapter 1. Introduction
Chapter 2. Overview of Supervised Learning
Chapter 3. Model Learning
Chapter 4. Basis Expansion & Regularization
Chapter 5. Model Selection
Chapter 6. Feature Selection
Chapter 7. Data Preparation
II. ADVANCED SUPERVISED LEARNING ALGORITHMS (WIP)
Chapter 1. Regression Models
Chapter 2. Logit Models
Chapter 3. Bayesian Models
Chapter 4. Maximum Margin Models
Chapter 5. Tree-Based Models
Chapter 6. Ensemble Models
Chapter 7. Algorithms Selection
Chapter 8. Hyperparameter Tuning
Chapter 9. Evaluation Metrics
Read for free: https://themlsbook.com/read
Buy on Amazon: https://www.amazon.com/dp/B0B216KMM4/qid=1653304321
Buy on LeanPub: https://leanpub.com/themlsbook
Repository: https://code.themlsbook.com/
Navigational hashtags: #armknowledgesharing #armbooks
General hashtags: #machinelearning #ml #algorithms #learning #book
@data_science_weekly