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An Introduction to Statistical Learning notes (1st edition)
Gareth James, Daniela Witten - ISBN: 9781461471370
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View all 11 notes for An Introduction to Statistical Learning, written by Gareth James, Daniela Witten. All An Introduction to Statistical Learning notes, flashcards, summaries and study guides are written by your fellow students or tutors. Get yourself a An Introduction to Statistical Learning summary or other study material that matches your study style perfectly, and studying will be a breeze.
Best selling An Introduction to Statistical Learning notes
Summary for the midterm of the course 'Business Analytics'. Includes all the reading material for week 1, 2, and 3. Week 1 --> Read chapter 2.1-2.2. Week 2 --> Read chapter 10.1, 10.3 Week 3 --> Read chapter 3.1-3.3, 3.5 Also, check out my free summary of the knowledge clips from week 1 till week 3!
- Summary
- • 22 pages •
Summary for the midterm of the course 'Business Analytics'. Includes all the reading material for week 1, 2, and 3. Week 1 --> Read chapter 2.1-2.2. Week 2 --> Read chapter 10.1, 10.3 Week 3 --> Read chapter 3.1-3.3, 3.5 Also, check out my free summary of the knowledge clips from week 1 till week 3!
This is a summary of the Data Analysis and Visualisation course taught at Utrecht University as part of the Applied Data Science (ADS) profile. Its contents are an extensive yet comprehensive summary of all chapters of the book Introduction to Statistical Learning (James et al.) and relevant papers. Topics touched upon are, among others, regression (linear and logistic), resampling, tree-based methods, classification, PCA, correspondence analysis, and cluster analysis.
- Summary
- • 41 pages •
This is a summary of the Data Analysis and Visualisation course taught at Utrecht University as part of the Applied Data Science (ADS) profile. Its contents are an extensive yet comprehensive summary of all chapters of the book Introduction to Statistical Learning (James et al.) and relevant papers. Topics touched upon are, among others, regression (linear and logistic), resampling, tree-based methods, classification, PCA, correspondence analysis, and cluster analysis.
Part 2 of the summary for the course 'Business Analytics'. Includes all the reading material for week 5, 6, and 7. Week 5 --> Read chapter 4.1-4.3 Week 6 --> Read chapter 5.1-5.2 Week 7 --> Read chapter 8.1-8.2.2
- Summary
- • 17 pages •
Part 2 of the summary for the course 'Business Analytics'. Includes all the reading material for week 5, 6, and 7. Week 5 --> Read chapter 4.1-4.3 Week 6 --> Read chapter 5.1-5.2 Week 7 --> Read chapter 8.1-8.2.2
Summary of Introduction to Statistical Learning. Includes graphs examples from the book. Chapter 2, 3, 4, 5, 7
- Summary
- • 15 pages •
Summary of Introduction to Statistical Learning. Includes graphs examples from the book. Chapter 2, 3, 4, 5, 7
This extensive summary contains all the theory presented in the JBM050 Statistical Computing course given at the TU/e in cooperation with TiU in 2020/2021. It also includes examples and pseudocode to help you prepare well for the assignments and the exam!
- Summary
- • 31 pages •
This extensive summary contains all the theory presented in the JBM050 Statistical Computing course given at the TU/e in cooperation with TiU in 2020/2021. It also includes examples and pseudocode to help you prepare well for the assignments and the exam!
Samenvatting of An Introduction to Statistical Learning - ISBN: 1370 Big Data Analysis (7204MM17XY), Hoofdstuk 2-10. Exclusief algorithmes, inclusief functiebeschrijvingen en visualisaties voor duidelijkheid.
- Summary
- • 14 pages •
Samenvatting of An Introduction to Statistical Learning - ISBN: 1370 Big Data Analysis (7204MM17XY), Hoofdstuk 2-10. Exclusief algorithmes, inclusief functiebeschrijvingen en visualisaties voor duidelijkheid.
Summary of part of the lecture slides of the course Machine Learning using the book of G. James, D. Witten, T. Hastie and R. Tibshirani, called 'An Introduction to Statistical Learning - with Applications in R,'. This course is taught at the Erasmus University Rotterdam as part of the Master Econometrics and Management Science.
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- • 24 pages •
Summary of part of the lecture slides of the course Machine Learning using the book of G. James, D. Witten, T. Hastie and R. Tibshirani, called 'An Introduction to Statistical Learning - with Applications in R,'. This course is taught at the Erasmus University Rotterdam as part of the Master Econometrics and Management Science.
This is a full word document answer sheet for the assignment IOP2601 ASSIGNMENT 2 which due in June 2020. The assignment is well and professionally done and ready to submit.
- Answers
- • 7 pages •
This is a full word document answer sheet for the assignment IOP2601 ASSIGNMENT 2 which due in June 2020. The assignment is well and professionally done and ready to submit.
These are my notes of Linear regression which I prepared while learning data science and its various algorithms. They are very good and clear with all the basics. My juniors also referred the same botes and they are also learning data science now. They are well writen and well synthesized. You can also refer to them if you want to learn and understand linear regression algorithm in an easy and efficient manner.
- Class notes
- • 5 pages •
These are my notes of Linear regression which I prepared while learning data science and its various algorithms. They are very good and clear with all the basics. My juniors also referred the same botes and they are also learning data science now. They are well writen and well synthesized. You can also refer to them if you want to learn and understand linear regression algorithm in an easy and efficient manner.
Essential notes by me from the course book
- Class notes
- • 80 pages •
Essential notes by me from the course book
Do you have documents that match this book? Sell them and earn money with your knowledge!
Newest An Introduction to Statistical Learning summaries
Summary for the midterm of the course 'Business Analytics'. Includes all the reading material for week 1, 2, and 3. Week 1 --> Read chapter 2.1-2.2. Week 2 --> Read chapter 10.1, 10.3 Week 3 --> Read chapter 3.1-3.3, 3.5 Also, check out my free summary of the knowledge clips from week 1 till week 3!
- Summary
- • 22 pages •
Summary for the midterm of the course 'Business Analytics'. Includes all the reading material for week 1, 2, and 3. Week 1 --> Read chapter 2.1-2.2. Week 2 --> Read chapter 10.1, 10.3 Week 3 --> Read chapter 3.1-3.3, 3.5 Also, check out my free summary of the knowledge clips from week 1 till week 3!
Part 2 of the summary for the course 'Business Analytics'. Includes all the reading material for week 5, 6, and 7. Week 5 --> Read chapter 4.1-4.3 Week 6 --> Read chapter 5.1-5.2 Week 7 --> Read chapter 8.1-8.2.2
- Summary
- • 17 pages •
Part 2 of the summary for the course 'Business Analytics'. Includes all the reading material for week 5, 6, and 7. Week 5 --> Read chapter 4.1-4.3 Week 6 --> Read chapter 5.1-5.2 Week 7 --> Read chapter 8.1-8.2.2
Summary of Introduction to Statistical Learning. Includes graphs examples from the book. Chapter 2, 3, 4, 5, 7
- Summary
- • 15 pages •
Summary of Introduction to Statistical Learning. Includes graphs examples from the book. Chapter 2, 3, 4, 5, 7
This extensive summary contains all the theory presented in the JBM050 Statistical Computing course given at the TU/e in cooperation with TiU in 2020/2021. It also includes examples and pseudocode to help you prepare well for the assignments and the exam!
- Summary
- • 31 pages •
This extensive summary contains all the theory presented in the JBM050 Statistical Computing course given at the TU/e in cooperation with TiU in 2020/2021. It also includes examples and pseudocode to help you prepare well for the assignments and the exam!
Samenvatting of An Introduction to Statistical Learning - ISBN: 1370 Big Data Analysis (7204MM17XY), Hoofdstuk 2-10. Exclusief algorithmes, inclusief functiebeschrijvingen en visualisaties voor duidelijkheid.
- Summary
- • 14 pages •
Samenvatting of An Introduction to Statistical Learning - ISBN: 1370 Big Data Analysis (7204MM17XY), Hoofdstuk 2-10. Exclusief algorithmes, inclusief functiebeschrijvingen en visualisaties voor duidelijkheid.
Summary of part of the lecture slides of the course Machine Learning using the book of G. James, D. Witten, T. Hastie and R. Tibshirani, called 'An Introduction to Statistical Learning - with Applications in R,'. This course is taught at the Erasmus University Rotterdam as part of the Master Econometrics and Management Science.
- Summary
- • 24 pages •
Summary of part of the lecture slides of the course Machine Learning using the book of G. James, D. Witten, T. Hastie and R. Tibshirani, called 'An Introduction to Statistical Learning - with Applications in R,'. This course is taught at the Erasmus University Rotterdam as part of the Master Econometrics and Management Science.
This is a full word document answer sheet for the assignment IOP2601 ASSIGNMENT 2 which due in June 2020. The assignment is well and professionally done and ready to submit.
- Answers
- • 7 pages •
This is a full word document answer sheet for the assignment IOP2601 ASSIGNMENT 2 which due in June 2020. The assignment is well and professionally done and ready to submit.
These are my notes of Linear regression which I prepared while learning data science and its various algorithms. They are very good and clear with all the basics. My juniors also referred the same botes and they are also learning data science now. They are well writen and well synthesized. You can also refer to them if you want to learn and understand linear regression algorithm in an easy and efficient manner.
- Class notes
- • 5 pages •
These are my notes of Linear regression which I prepared while learning data science and its various algorithms. They are very good and clear with all the basics. My juniors also referred the same botes and they are also learning data science now. They are well writen and well synthesized. You can also refer to them if you want to learn and understand linear regression algorithm in an easy and efficient manner.
ISBN: 9781461471370 Big Data Analysis (7204MM17XY): H1 t/m 7
- Summary
- • 7 pages •
ISBN: 9781461471370 Big Data Analysis (7204MM17XY): H1 t/m 7
Essential notes by me from the course book
- Class notes
- • 80 pages •
Essential notes by me from the course book
Do you have documents that match this book? Sell them and earn money with your knowledge!
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