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[FreeCoursesOnline.Me] Coursera - Applied Machine Learning in Python
- Date: 2023-10-02
- Size: 881 MB
- Files: 73
File Name
Size
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/001. Introduction.mp4
31 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/001. Introduction.srt
16 kB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/002. Key Concepts in Machine Learning.mp4
45 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/002. Key Concepts in Machine Learning.srt
19 kB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/003. Python Tools for Machine Learning.mp4
13 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/003. Python Tools for Machine Learning.srt
6.1 kB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/004. An Example Machine Learning Problem.mp4
32 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/004. An Example Machine Learning Problem.srt
15 kB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/005. Examining the Data.mp4
32 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/005. Examining the Data.srt
12 kB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/006. K-Nearest Neighbors Classification.mp4
36 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/006. K-Nearest Neighbors Classification.srt
26 kB
002.Module 2 Supervised Machine Learning/007. Introduction to Supervised Machine Learning.mp4
38 MB
002.Module 2 Supervised Machine Learning/007. Introduction to Supervised Machine Learning.srt
22 kB
002.Module 2 Supervised Machine Learning/008. Overfitting and Underfitting.mp4
20 MB
002.Module 2 Supervised Machine Learning/008. Overfitting and Underfitting.srt
16 kB
002.Module 2 Supervised Machine Learning/009. Supervised Learning Datasets.mp4
11 MB
002.Module 2 Supervised Machine Learning/009. Supervised Learning Datasets.srt
6.7 kB
002.Module 2 Supervised Machine Learning/010. K-Nearest Neighbors Classification and Regression.mp4
22 MB
002.Module 2 Supervised Machine Learning/010. K-Nearest Neighbors Classification and Regression.srt
17 kB
002.Module 2 Supervised Machine Learning/011. Linear Regression Least-Squares.mp4
30 MB
002.Module 2 Supervised Machine Learning/011. Linear Regression Least-Squares.srt
21 kB
002.Module 2 Supervised Machine Learning/012. Linear Regression Ridge, Lasso, and Polynomial Regression.mp4
40 MB
002.Module 2 Supervised Machine Learning/012. Linear Regression Ridge, Lasso, and Polynomial Regression.srt
27 kB
002.Module 2 Supervised Machine Learning/013. Logistic Regression.mp4
20 MB
002.Module 2 Supervised Machine Learning/013. Logistic Regression.srt
17 kB
002.Module 2 Supervised Machine Learning/014. Linear Classifiers Support Vector Machines.mp4
23 MB
002.Module 2 Supervised Machine Learning/014. Linear Classifiers Support Vector Machines.srt
16 kB
002.Module 2 Supervised Machine Learning/015. Multi-Class Classification.mp4
15 MB
002.Module 2 Supervised Machine Learning/015. Multi-Class Classification.srt
8.3 kB
002.Module 2 Supervised Machine Learning/016. Kernelized Support Vector Machines.mp4
39 MB
002.Module 2 Supervised Machine Learning/016. Kernelized Support Vector Machines.srt
26 kB
002.Module 2 Supervised Machine Learning/017. Cross-Validation.mp4
20 MB
002.Module 2 Supervised Machine Learning/017. Cross-Validation.srt
13 kB
002.Module 2 Supervised Machine Learning/018. Decision Trees.mp4
38 MB
002.Module 2 Supervised Machine Learning/018. Decision Trees.srt
28 kB
003.Module 3 Evaluation/019. Model Evaluation & Selection.mp4
46 MB
003.Module 3 Evaluation/019. Model Evaluation & Selection.srt
30 kB
003.Module 3 Evaluation/020. Confusion Matrices & Basic Evaluation Metrics.mp4
21 MB
003.Module 3 Evaluation/020. Confusion Matrices & Basic Evaluation Metrics.srt
16 kB
003.Module 3 Evaluation/021. Classifier Decision Functions.mp4
13 MB
003.Module 3 Evaluation/021. Classifier Decision Functions.srt
9.0 kB
003.Module 3 Evaluation/022. Precision-recall and ROC curves.mp4
9.2 MB
003.Module 3 Evaluation/022. Precision-recall and ROC curves.srt
7.5 kB
003.Module 3 Evaluation/023. Multi-Class Evaluation.mp4
20 MB
003.Module 3 Evaluation/023. Multi-Class Evaluation.srt
15 kB
003.Module 3 Evaluation/024. Regression Evaluation.mp4
17 MB
003.Module 3 Evaluation/024. Regression Evaluation.srt
7.8 kB
003.Module 3 Evaluation/025. Model Selection Optimizing Classifiers for Different Evaluation Metrics.mp4
34 MB
003.Module 3 Evaluation/025. Model Selection Optimizing Classifiers for Different Evaluation Metrics.srt
18 kB
004.Module 4 Supervised Machine Learning - Part 2/026. Naive Bayes Classifiers.mp4
21 MB
004.Module 4 Supervised Machine Learning - Part 2/026. Naive Bayes Classifiers.srt
11 kB
004.Module 4 Supervised Machine Learning - Part 2/027. Random Forests.mp4
26 MB
004.Module 4 Supervised Machine Learning - Part 2/027. Random Forests.srt
17 kB
004.Module 4 Supervised Machine Learning - Part 2/028. Gradient Boosted Decision Trees.mp4
12 MB
004.Module 4 Supervised Machine Learning - Part 2/028. Gradient Boosted Decision Trees.srt
8.4 kB
004.Module 4 Supervised Machine Learning - Part 2/029. Neural Networks.mp4
42 MB
004.Module 4 Supervised Machine Learning - Part 2/029. Neural Networks.srt
28 kB
004.Module 4 Supervised Machine Learning - Part 2/030. Deep Learning (Optional).mp4
18 MB
004.Module 4 Supervised Machine Learning - Part 2/030. Deep Learning (Optional).srt
10 kB
004.Module 4 Supervised Machine Learning - Part 2/031. Data Leakage.mp4
33 MB
004.Module 4 Supervised Machine Learning - Part 2/031. Data Leakage.srt
17 kB
005.Optional Unsupervised Machine Learning/032. Introduction.mp4
11 MB
005.Optional Unsupervised Machine Learning/032. Introduction.srt
6.5 kB
005.Optional Unsupervised Machine Learning/033. Dimensionality Reduction and Manifold Learning.mp4
16 MB
005.Optional Unsupervised Machine Learning/033. Dimensionality Reduction and Manifold Learning.srt
14 kB
005.Optional Unsupervised Machine Learning/034. Clustering.mp4
27 MB
005.Optional Unsupervised Machine Learning/034. Clustering.srt
20 kB
006.Conclusion/035. Conclusion.mp4
9.9 MB
006.Conclusion/035. Conclusion.srt
3.9 kB
[FreeCoursesOnline.Me].url
133 B
[FreeTutorials.Us].url
119 B
[FTU Forum].url
252 B