Skip to content
Course Study Tracker [Coda Doctorate 2022 Capstone]
Introduction
Studying Process
Setup
More
Share
Explore
Studying Process

icon picker
Progress

Course:
◀
⁠
⁠
02. ML
⁠
⁠
▶
⁠
⁠

Course
Module
✔️
Lesson
Completed
Unclarity
Comments
Last Study
Summary Link
Completeness of Summary
Value
02. ML
35
Module 1. Machine Learning Theory
13
​
1.1. What is this module about?

Open
01/08/2022
000
100
​
1.2. Algorithms types

Open
01/08/2022
000
100
​
1.3. Machine learning tasks

Open
01/08/2022
000
100
​
1.4. FAQ

Open
01/08/2022
000
100
​
1.5. Task Development Methodology

Open
01/08/2022
000
100
​
1.6. Definition of business requirements

Open
01/08/2022
000
100
​
1.7. Data collection and preparation

Open
01/08/2022
000
100
​
1.8. Model development
! Read more about Loss function [
>>
⁠
]
! Finish the outline
Open
01/08/2022
000
75
​
1.9. Model testing and implementation
! Alternating Least Square (ALS) Matrix Factorization ?
Figure out how to actually run lightfm from a docker container
— you need to fix the port in docker-compose.yml so that it doesn’t intersect with JN on localhost
Open
01/08/2022
000
75
​
1.10. Modeling Challenges
“Bad precision or bad recall doesn't mean you'll get bad embeddings. This is a consequence of the model being trained through the ALS algorithm, which uses a different quality metric when training.”
Open
01/08/2022
000
100
​
1.11. Tips & Lifehacks

Open
000
​
1.12. Jupyter

Open
000
​
1.13. Modeling process

Open
000
Module 2. Data preprocessing methods
13
​
2.1. What is this module about?

Open
01/08/2022
000
​
2.2. Data types

Open
01/08/2022
000
​
2.3. Data issues

Open
01/08/2022
000
​
2.4. Work with gaps

Open
01/08/2022
000
​
2.5. Practice

Open
01/08/2022
000
​
2.6. Initial processing

Open
01/08/2022
000
​
2.7. Practice

Open
01/08/2022
000
​
2.8. Visualization
* A noteworthy point: "throwing out" features with a very high correlation
Open
01/08/2022
000
​
2.9. Practice
! Finish the outline
Open
01/08/2022
000
​
2.10. Feature Engineering
! Finish the outline
Open
01/08/2022
000
​
2.11. Practice
! Need to better understand the polynomial features
Excercise 2.11.6: ?? [
>>
⁠
]
Open
01/08/2022
000
​
2.12. Looking for outliers

Open
01/08/2022
000
​
2.13. Practice
! Better clarify the z-score, IQR !
Excercise 2.13.2: ?
⁠
maxtrixcalc
⁠
⁠
Open
01/08/2022
000
Module 3. Regression
9
​
3.1. What is this module about?

Open
01/08/2022
000
100
​
3.2. Linear Regression

Open
01/08/2022
000
100
​
3.3. Errors in Linear Regression
!! Take a deeper dive into bias and variance
Open
01/08/2022
000
75
​
3.4. Searching for the line
! Better figure out the essence of Coefficient of determination
Open
01/08/2022
000
75
​
3.5. Linear regression. Practice #1

Open
01/08/2022
000
100
​
3.6. Linear regression. Practice #2

Open
01/08/2022
000
100
​
3.7. Logistic regression. Part 1
* Nice detailed video
More digging into softmax
Summarize cross-validation
Open
01/08/2022
000
100
​
3.8. Logistic regression. Part 2
Regularization (L1 and L2) techniques to avoid over-fitting?
Impact of outliers?

! Finish the outline
Open
01/08/2022
000
25
​
3.9. Logistic regression. Practice
! Finish the outline
Open
01/08/2022
000
25
⁠
Want to print your doc?
This is not the way.
Try clicking the ⋯ next to your doc name or using a keyboard shortcut (
CtrlP
) instead.