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003.Module 3 Evaluation/019. Model Evaluation & Selection.mp4 46.1 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/002. Key Concepts in Machine Learning.mp4 44.56 MB
004.Module 4 Supervised Machine Learning - Part 2/029. Neural Networks.mp4 41.51 MB
002.Module 2 Supervised Machine Learning/012. Linear Regression Ridge, Lasso, and Polynomial Regression.mp4 39.93 MB
002.Module 2 Supervised Machine Learning/016. Kernelized Support Vector Machines.mp4 39.14 MB
002.Module 2 Supervised Machine Learning/007. Introduction to Supervised Machine Learning.mp4 37.88 MB
002.Module 2 Supervised Machine Learning/018. Decision Trees.mp4 37.83 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/006. K-Nearest Neighbors Classification.mp4 36.25 MB
003.Module 3 Evaluation/025. Model Selection Optimizing Classifiers for Different Evaluation Metrics.mp4 34.5 MB
004.Module 4 Supervised Machine Learning - Part 2/031. Data Leakage.mp4 32.89 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/005. Examining the Data.mp4 32.24 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/004. An Example Machine Learning Problem.mp4 31.73 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/001. Introduction.mp4 31.05 MB
002.Module 2 Supervised Machine Learning/011. Linear Regression Least-Squares.mp4 30.08 MB
005.Optional Unsupervised Machine Learning/034. Clustering.mp4 27.18 MB
004.Module 4 Supervised Machine Learning - Part 2/027. Random Forests.mp4 26.45 MB
002.Module 2 Supervised Machine Learning/014. Linear Classifiers Support Vector Machines.mp4 22.69 MB
002.Module 2 Supervised Machine Learning/010. K-Nearest Neighbors Classification and Regression.mp4 22.53 MB
004.Module 4 Supervised Machine Learning - Part 2/026. Naive Bayes Classifiers.mp4 21.38 MB
003.Module 3 Evaluation/020. Confusion Matrices & Basic Evaluation Metrics.mp4 20.75 MB
002.Module 2 Supervised Machine Learning/013. Logistic Regression.mp4 20.3 MB
002.Module 2 Supervised Machine Learning/017. Cross-Validation.mp4 20 MB
003.Module 3 Evaluation/023. Multi-Class Evaluation.mp4 19.77 MB
002.Module 2 Supervised Machine Learning/008. Overfitting and Underfitting.mp4 19.51 MB
004.Module 4 Supervised Machine Learning - Part 2/030. Deep Learning (Optional).mp4 17.46 MB
003.Module 3 Evaluation/024. Regression Evaluation.mp4 17.01 MB
005.Optional Unsupervised Machine Learning/033. Dimensionality Reduction and Manifold Learning.mp4 16.09 MB
002.Module 2 Supervised Machine Learning/015. Multi-Class Classification.mp4 15.41 MB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/003. Python Tools for Machine Learning.mp4 12.86 MB
003.Module 3 Evaluation/021. Classifier Decision Functions.mp4 12.65 MB
004.Module 4 Supervised Machine Learning - Part 2/028. Gradient Boosted Decision Trees.mp4 11.81 MB
002.Module 2 Supervised Machine Learning/009. Supervised Learning Datasets.mp4 11.22 MB
005.Optional Unsupervised Machine Learning/032. Introduction.mp4 10.67 MB
006.Conclusion/035. Conclusion.mp4 9.89 MB
003.Module 3 Evaluation/022. Precision-recall and ROC curves.mp4 9.23 MB
003.Module 3 Evaluation/019. Model Evaluation & Selection.srt 30.08 KB
002.Module 2 Supervised Machine Learning/018. Decision Trees.srt 28.36 KB
004.Module 4 Supervised Machine Learning - Part 2/029. Neural Networks.srt 27.9 KB
002.Module 2 Supervised Machine Learning/012. Linear Regression Ridge, Lasso, and Polynomial Regression.srt 27.19 KB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/006. K-Nearest Neighbors Classification.srt 26.19 KB
002.Module 2 Supervised Machine Learning/016. Kernelized Support Vector Machines.srt 25.6 KB
002.Module 2 Supervised Machine Learning/007. Introduction to Supervised Machine Learning.srt 22.13 KB
002.Module 2 Supervised Machine Learning/011. Linear Regression Least-Squares.srt 21.26 KB
005.Optional Unsupervised Machine Learning/034. Clustering.srt 19.9 KB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/002. Key Concepts in Machine Learning.srt 18.82 KB
003.Module 3 Evaluation/025. Model Selection Optimizing Classifiers for Different Evaluation Metrics.srt 18.12 KB
002.Module 2 Supervised Machine Learning/013. Logistic Regression.srt 17.13 KB
002.Module 2 Supervised Machine Learning/010. K-Nearest Neighbors Classification and Regression.srt 17.09 KB
004.Module 4 Supervised Machine Learning - Part 2/027. Random Forests.srt 17.07 KB
004.Module 4 Supervised Machine Learning - Part 2/031. Data Leakage.srt 16.69 KB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/001. Introduction.srt 16.07 KB
003.Module 3 Evaluation/020. Confusion Matrices & Basic Evaluation Metrics.srt 15.85 KB
002.Module 2 Supervised Machine Learning/008. Overfitting and Underfitting.srt 15.81 KB
002.Module 2 Supervised Machine Learning/014. Linear Classifiers Support Vector Machines.srt 15.54 KB
003.Module 3 Evaluation/023. Multi-Class Evaluation.srt 15.21 KB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/004. An Example Machine Learning Problem.srt 14.83 KB
005.Optional Unsupervised Machine Learning/033. Dimensionality Reduction and Manifold Learning.srt 13.47 KB
002.Module 2 Supervised Machine Learning/017. Cross-Validation.srt 13 KB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/005. Examining the Data.srt 12.05 KB
004.Module 4 Supervised Machine Learning - Part 2/026. Naive Bayes Classifiers.srt 11.2 KB
004.Module 4 Supervised Machine Learning - Part 2/030. Deep Learning (Optional).srt 10.34 KB
003.Module 3 Evaluation/021. Classifier Decision Functions.srt 9.04 KB
004.Module 4 Supervised Machine Learning - Part 2/028. Gradient Boosted Decision Trees.srt 8.44 KB
002.Module 2 Supervised Machine Learning/015. Multi-Class Classification.srt 8.3 KB
003.Module 3 Evaluation/024. Regression Evaluation.srt 7.83 KB
003.Module 3 Evaluation/022. Precision-recall and ROC curves.srt 7.53 KB
002.Module 2 Supervised Machine Learning/009. Supervised Learning Datasets.srt 6.74 KB
005.Optional Unsupervised Machine Learning/032. Introduction.srt 6.46 KB
001.Module 1 Fundamentals of Machine Learning - Intro to SciKit Learn/003. Python Tools for Machine Learning.srt 6.11 KB
006.Conclusion/035. Conclusion.srt 3.9 KB
[FTU Forum].url 252 B
[FreeCoursesOnline.Me].url 133 B
[FreeTutorials.Us].url 119 B
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