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种子名称:
[GigaCourse.Com] Udemy - The Supervised Machine Learning Course
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视频
文件数目:
75个文件
文件大小:
2.68 GB
收录时间:
2023-9-9 00:37
已经下载:
3次
资源热度:
92
最近下载:
2024-12-18 02:49
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[GigaCourse.Com] Udemy - The Supervised Machine Learning Course.torrent
1 - Introduction/1 - Introduction.mp469.89MB
2 - Setting up the Environment/2 - Installing Anaconda.mp429.53MB
2 - Setting up the Environment/3 - Jupyter Dashboard Part 1.mp410.25MB
2 - Setting up the Environment/4 - Jupyter Dashboard Part 2.mp420.99MB
2 - Setting up the Environment/5 - Installing the relevant packages.mp422.78MB
3 - Naïve Bayes/10 - The HamorSpam Example.mp466.89MB
3 - Naïve Bayes/12 - The YouTube Dataset Creating the Data Frame.mp433.75MB
3 - Naïve Bayes/13 - CountVectorizer.mp436.99MB
3 - Naïve Bayes/14 - The YouTube Dataset Preprocessing.mp443.97MB
3 - Naïve Bayes/16 - The YouTube Dataset Classification.mp423.67MB
3 - Naïve Bayes/18 - The YouTube Dataset Confusion Matrix.mp417.79MB
3 - Naïve Bayes/19 - The YouTube Dataset Accuracy Precision Recall and the F1 score.mp437.74MB
3 - Naïve Bayes/20 - The YouTube Dataset Changing the Priors.mp440.34MB
3 - Naïve Bayes/6 - Motivation.mp443.38MB
3 - Naïve Bayes/7 - Bayes Thought Experiment.mp433.66MB
3 - Naïve Bayes/9 - Bayes Theorem.mp465.92MB
4 - KNearest Neighbors/22 - Motivation.mp424.43MB
4 - KNearest Neighbors/23 - Math Prerequisites Distance Metrics.mp427.79MB
4 - KNearest Neighbors/24 - Random Dataset Generating the Dataset.mp416.85MB
4 - KNearest Neighbors/25 - Random Dataset Visualizing the Dataset.mp428.19MB
4 - KNearest Neighbors/26 - Random Dataset Classification.mp450.6MB
4 - KNearest Neighbors/27 - Random Dataset How to Break a Tie.mp426.76MB
4 - KNearest Neighbors/28 - Random Dataset Decision Regions.mp446MB
4 - KNearest Neighbors/29 - Random Dataset Choosing the Best Kvalue.mp432.64MB
4 - KNearest Neighbors/30 - Random Dataset Grid Search.mp427.88MB
4 - KNearest Neighbors/31 - Random Dataset Model Performance.mp421.21MB
4 - KNearest Neighbors/33 - Theory with a Practical Example.mp443.75MB
4 - KNearest Neighbors/34 - KNN vs Linear Regression A Linear Problem.mp446.73MB
4 - KNearest Neighbors/35 - KNN vs Linear Regression A Nonlinear Problem.mp433.11MB
4 - KNearest Neighbors/37 - Pros and Cons.mp455.22MB
5 - Decision Trees and Random Forests/38 - What is a Tree in Computer Science.mp434.84MB
5 - Decision Trees and Random Forests/39 - The Concept of Decision Trees.mp431.62MB
5 - Decision Trees and Random Forests/40 - Decision Trees in Machine Learning.mp447.34MB
5 - Decision Trees and Random Forests/41 - Decision Trees Pros and Cons.mp469.13MB
5 - Decision Trees and Random Forests/42 - Practical Example The Iris Dataset.mp421.83MB
5 - Decision Trees and Random Forests/43 - Practical Example Creating a Decision Tree.mp432.83MB
5 - Decision Trees and Random Forests/44 - Practical Example Plotting the Tree.mp442.97MB
5 - Decision Trees and Random Forests/45 - Decision Tree Metrics Intuition Gini Inpurity.mp453.2MB
5 - Decision Trees and Random Forests/46 - Decision Tree Metrics Information Gain.mp426.36MB
5 - Decision Trees and Random Forests/47 - Tree Pruning Dealing with Overfitting.mp439.41MB
5 - Decision Trees and Random Forests/48 - Random Forest as Ensemble Learning.mp431.99MB
5 - Decision Trees and Random Forests/49 - Bootstrapping.mp429.92MB
5 - Decision Trees and Random Forests/50 - From Bootstrapping to Random Forests.mp425.93MB
5 - Decision Trees and Random Forests/51 - Random Forest in Code Glass Dataset.mp452.81MB
5 - Decision Trees and Random Forests/52 - Census Data and Income Preprocessing.mp459.6MB
5 - Decision Trees and Random Forests/53 - Training the Decision Tree.mp427.35MB
5 - Decision Trees and Random Forests/54 - Training the Random Forest.mp427.17MB
6 - Support Vector Machines/55 - Introduction to Support Vector Machines.mp462.4MB
6 - Support Vector Machines/56 - Linearly separable classes hard margin problem.mp459.15MB
6 - Support Vector Machines/57 - Nonlinearly separable classes soft margin problem.mp449.84MB
6 - Support Vector Machines/58 - Kernels Intuition.mp477.05MB
6 - Support Vector Machines/59 - Intro to the practical case.mp431.54MB
6 - Support Vector Machines/60 - Preprocessing the data.mp415.06MB
6 - Support Vector Machines/61 - Splitting the data into train and test and rescaling.mp416.4MB
6 - Support Vector Machines/62 - Implementing a linear SVM.mp412.66MB
6 - Support Vector Machines/63 - Analyzing the results– Confusion Matrix Precision and Recall.mp428.22MB
6 - Support Vector Machines/64 - Crossvalidation.mp476.47MB
6 - Support Vector Machines/65 - Choosing the kernels and C values for crossvalidation.mp418.81MB
6 - Support Vector Machines/66 - Hyperparameter tuning using GridSearchCV.mp435.14MB
7 - Ridge and Lasso Regression/68 - Regression Analysis Overview.mp429.41MB
7 - Ridge and Lasso Regression/69 - Overfitting and Multicollinearity.mp428.15MB
7 - Ridge and Lasso Regression/70 - Introduction to Regularization.mp425.96MB
7 - Ridge and Lasso Regression/71 - Ridge Regression Basics.mp443.16MB
7 - Ridge and Lasso Regression/72 - Ridge Regression Mechanics.mp446.67MB
7 - Ridge and Lasso Regression/73 - Regularization in More Complicated Scenarios.mp421MB
7 - Ridge and Lasso Regression/74 - Lasso Regression Basics.mp421.63MB
7 - Ridge and Lasso Regression/75 - Lasso Regression vs Ridge Regression.mp433.86MB
7 - Ridge and Lasso Regression/76 - The Hitters Dataset Preprocessing and Preparation.mp446MB
7 - Ridge and Lasso Regression/77 - Exploratory Data Analysis.mp436.96MB
7 - Ridge and Lasso Regression/78 - Performing Linear Regression.mp452.93MB
7 - Ridge and Lasso Regression/79 - Crossvalidation for Choosing a Tuning Parameter.mp430.49MB
7 - Ridge and Lasso Regression/80 - Performing Ridge Regression with Crossvalidation.mp430.97MB
7 - Ridge and Lasso Regression/81 - Performing Lasso Regression with Crossvalidation.mp430.96MB
7 - Ridge and Lasso Regression/82 - Comparing the Results.mp430.97MB
7 - Ridge and Lasso Regression/83 - Replacing the Missing Values in the DataFrame.mp421.22MB