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[DesireCourse.Net] Udemy - Beginning with Machine Learning & Data Science in Python
magnet:?xt=urn:btih:c4db89131dae7b02aeff820353dd60dd92cade21&dn=[DesireCourse.Net] Udemy - Beginning with Machine Learning & Data Science in Python
磁力链接详情
Hash值:
c4db89131dae7b02aeff820353dd60dd92cade21
点击数:
119
文件大小:
531.1 MB
文件数量:
50
创建日期:
2021-3-25 12:31
最后访问:
2024-6-21 07:01
访问标签:
DesireCourse
Net
Udemy
-
Beginning
with
Machine
Learning
&
Data
Science
in
Python
文件列表详情
1. Working with Machine Learning/1. Exploring Machine Learning and its Types.mp4 7.32 MB
1. Working with Machine Learning/3. Install Anaconda.mp4 8.78 MB
1. Working with Machine Learning/5. Python and Jupyter Demo.mp4 17.69 MB
2. Understanding Data Wrangling/1. Introduction.mp4 498.56 KB
2. Understanding Data Wrangling/10. Summary.mp4 539.41 KB
2. Understanding Data Wrangling/2. Reading from a CSV.mp4 16.06 MB
2. Understanding Data Wrangling/3. Selecting data and finding the most common complaint type.mp4 25.11 MB
2. Understanding Data Wrangling/4. Which borough has the most noise complaints.mp4 19.48 MB
2. Understanding Data Wrangling/5. Which weekday do people bike the most.mp4 16.96 MB
2. Understanding Data Wrangling/6. Which month was the snowiest.mp4 20.43 MB
2. Understanding Data Wrangling/7. Cleaning Messy Data.mp4 32.02 MB
2. Understanding Data Wrangling/8. How to deal with timestamps.mp4 16.37 MB
2. Understanding Data Wrangling/8.2 popularity-contest.tsv.tsv 185.24 KB
2. Understanding Data Wrangling/9. Loading data from SQL databases.mp4 13.45 MB
3. Linear Regression/1. Introduction.mp4 1.74 MB
3. Linear Regression/10. Model evaluation.mp4 10.73 MB
3. Linear Regression/11. Handling categorical features.mp4 19.83 MB
3. Linear Regression/12. Summary.mp4 5.45 MB
3. Linear Regression/2. What is linear regression.mp4 2.83 MB
3. Linear Regression/3. The advertising dataset.mp4 7.09 MB
3. Linear Regression/4. EDA questions on advertising data.mp4 4.72 MB
3. Linear Regression/5. Simple Linear Regression.mp4 21.9 MB
3. Linear Regression/6. Hypothesis testing and p-values.mp4 7.83 MB
3. Linear Regression/7. R squared.mp4 5.77 MB
3. Linear Regression/8. Multiple linear regression.mp4 15.34 MB
3. Linear Regression/9. Model and feature selection.mp4 7.09 MB
4. Logistic Regression/1. Introduction.mp4 891.31 KB
4. Logistic Regression/10. Summary.mp4 896.84 KB
4. Logistic Regression/2. Predicting a continuous response.mp4 11.59 MB
4. Logistic Regression/3. Quick refresher on linear regression.mp4 4.9 MB
4. Logistic Regression/4. Predicting a categorical response.mp4 15.7 MB
4. Logistic Regression/5. Using logistic regression.mp4 11.37 MB
4. Logistic Regression/6. Probability, odds, log-odds.mp4 15.05 MB
4. Logistic Regression/7. What is logistic regression.mp4 10.91 MB
4. Logistic Regression/8. Interpreting logistic regression.mp4 16.3 MB
4. Logistic Regression/9. Using logistic regression with categorical features.mp4 7.25 MB
5. Cross Validation/1. Introduction.mp4 891.74 KB
5. Cross Validation/2. Traintest split.mp4 7.45 MB
5. Cross Validation/3. K-fold cross-validation.mp4 8.03 MB
5. Cross Validation/4. Cross-validation continued.mp4 15.89 MB
5. Cross Validation/5. Summary.mp4 4.87 MB
6. Regularization/1. Introduction.mp4 1.17 MB
6. Regularization/2. Overfitting.mp4 4.7 MB
6. Regularization/3. Overfitting with linear models.mp4 12.52 MB
6. Regularization/4. Regularizing linear models.mp4 16.89 MB
6. Regularization/5. Ridge and Lasso Regularization.mp4 8.86 MB
6. Regularization/6. Regularization using scikit-learn.mp4 22.89 MB
6. Regularization/7. Regularizing logistic models.mp4 11.18 MB
6. Regularization/8. Pipeline and GridSearchCV.mp4 12.59 MB
6. Regularization/9. Comparing regularized with unregularized models.mp4 3.22 MB
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