[FreeCourseLab.com] Udemy - Machine Learning & Data Science A-Z Hands-on Python 2021

磁力链接/BT种子名称

[FreeCourseLab.com] Udemy - Machine Learning & Data Science A-Z Hands-on Python 2021

磁力链接/BT种子简介

种子哈希：7af45a41189b125070a9d02b3eae7715afa5a960
文件大小： 6.75G
已经下载：455次
下载速度：极快
收录时间：2022-02-17
最近下载：2024-12-08

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文件列表

  • 06 Supervised Learning - Regression/008 Random Forest Model Development.mp4 258.2 MB
  • 05 Supervised Learning - Classification/001 Supervised Learning Models - Introduction and Understanding the Data.mp4 245.1 MB
  • 05 Supervised Learning - Classification/004 k-NN Training-Set and Test-Set Creation.mp4 239.5 MB
  • 03 Data Preprocessing/006 Missing Values2.mp4 230.0 MB
  • 06 Supervised Learning - Regression/006 Polynomial Linear Regression Model Development.mp4 229.8 MB
  • 06 Supervised Learning - Regression/001 Simple and Multiple Linear Regression Concepts.mp4 222.5 MB
  • 03 Data Preprocessing/003 Statistics2.mp4 217.6 MB
  • 02 Machine Learning Useful Packages (Libraries)/013 Visualization with Matplotlib2.mp4 215.2 MB
  • 02 Machine Learning Useful Packages (Libraries)/011 Pandas4.mp4 212.9 MB
  • 02 Machine Learning Useful Packages (Libraries)/014 Visualization with Matplotlib3.mp4 198.0 MB
  • 03 Data Preprocessing/012 Normalization.mp4 195.9 MB
  • 05 Supervised Learning - Classification/013 Model Evaluation - Calculating with Python.mp4 182.5 MB
  • 06 Supervised Learning - Regression/004 Evaluation Metrics - Implementation.mp4 167.7 MB
  • 03 Data Preprocessing/001 Reading and Modifying a Dataset.mp4 162.1 MB
  • 02 Machine Learning Useful Packages (Libraries)/006 NumPy5.mp4 160.1 MB
  • 07 Unsupervised Learning - Clustering Techniques/010 Hierarchical Clustering Model Development.mp4 153.0 MB
  • 02 Machine Learning Useful Packages (Libraries)/015 Visualization with Matplotlib4.mp4 149.9 MB
  • 05 Supervised Learning - Classification/003 k-NN Model Development.mp4 147.5 MB
  • 02 Machine Learning Useful Packages (Libraries)/007 NumPy6.mp4 141.0 MB
  • 08 Hyper Parameter Optimization (Model Tuning)/004 k-NN - Model Tuning.mp4 140.1 MB
  • 03 Data Preprocessing/008 Outlier Detection2.mp4 137.0 MB
  • 03 Data Preprocessing/005 Missing Values1.mp4 135.9 MB
  • 02 Machine Learning Useful Packages (Libraries)/016 Visualization with Matplotlib5.mp4 135.5 MB
  • 08 Hyper Parameter Optimization (Model Tuning)/002 Support Vector Regression - Model Tuning.mp4 131.7 MB
  • 06 Supervised Learning - Regression/010 Support Vector Regression Model Development.mp4 126.9 MB
  • 02 Machine Learning Useful Packages (Libraries)/010 Pandas3.mp4 123.6 MB
  • 02 Machine Learning Useful Packages (Libraries)/009 Pandas2.mp4 122.6 MB
  • 05 Supervised Learning - Classification/011 Logistic Regression Model Development.mp4 117.6 MB
  • 03 Data Preprocessing/004 Statistics3 - Covariance.mp4 112.7 MB
  • 07 Unsupervised Learning - Clustering Techniques/005 K-means Model Development2.mp4 108.9 MB
  • 07 Unsupervised Learning - Clustering Techniques/006 K-means - Model Evaluation.mp4 107.4 MB
  • 02 Machine Learning Useful Packages (Libraries)/012 Visualization with Matplotlib1.mp4 104.3 MB
  • 02 Machine Learning Useful Packages (Libraries)/008 Pandas1.mp4 100.3 MB
  • 07 Unsupervised Learning - Clustering Techniques/008 DBSCAN Model Development.mp4 91.1 MB
  • 02 Machine Learning Useful Packages (Libraries)/004 NumPy3.mp4 88.6 MB
  • 05 Supervised Learning - Classification/012 Model Evaluation Concepts.mp4 87.5 MB
  • 06 Supervised Learning - Regression/002 Multiple Linear Regression - Model Development.mp4 79.3 MB
  • 03 Data Preprocessing/007 Outlier Detection1.mp4 76.8 MB
  • 08 Hyper Parameter Optimization (Model Tuning)/005 Overfitting and Underfitting.mp4 75.6 MB
  • 01 Introduction/006 Installation of Required Libraries.mp4 74.2 MB
  • 05 Supervised Learning - Classification/006 Decision Tree Model Development.mp4 70.1 MB
  • 03 Data Preprocessing/010 Concatenation.mp4 69.1 MB
  • 05 Supervised Learning - Classification/008 Naive Bayes Concepts.mp4 62.1 MB
  • 05 Supervised Learning - Classification/009 Naive Bayes Model Development.mp4 61.8 MB
  • 03 Data Preprocessing/011 Dummy Variable.mp4 60.4 MB
  • 02 Machine Learning Useful Packages (Libraries)/003 NumPy2.mp4 59.7 MB
  • 02 Machine Learning Useful Packages (Libraries)/005 NumPy4.mp4 59.3 MB
  • 05 Supervised Learning - Classification/007 Decision Tree - Cross Validation.mp4 57.3 MB
  • 06 Supervised Learning - Regression/003 Evaluation Metrics - Concepts.mp4 51.9 MB
  • 05 Supervised Learning - Classification/002 k-NN Concepts.mp4 50.4 MB
  • 01 Introduction/007 Spyder Interface.mp4 48.6 MB
  • 04 Machine Learning Introduction/001 Learning Types.mp4 47.6 MB
  • 07 Unsupervised Learning - Clustering Techniques/002 K-means Concepts1.mp4 46.7 MB
  • 07 Unsupervised Learning - Clustering Techniques/001 Introduction.mp4 40.0 MB
  • 02 Machine Learning Useful Packages (Libraries)/002 NumPy1.mp4 39.3 MB
  • 07 Unsupervised Learning - Clustering Techniques/004 K-means Model Development1.mp4 37.7 MB
  • 03 Data Preprocessing/002 Statistics1.mp4 35.7 MB
  • 03 Data Preprocessing/009 Outlier Detection3.mp4 32.5 MB
  • 06 Supervised Learning - Regression/007 Random Forest Concepts.mp4 31.7 MB
  • 06 Supervised Learning - Regression/009 Support Vector Regression Concepts.mp4 28.3 MB
  • 07 Unsupervised Learning - Clustering Techniques/007 DBSCAN Concepts.mp4 28.2 MB
  • 06 Supervised Learning - Regression/005 Polynomial Linear Regression Concepts.mp4 27.7 MB
  • 01 Introduction/002 What is Machine Learning_ Some Basic Terms.mp4 27.1 MB
  • 05 Supervised Learning - Classification/005 Decision Tree Concepts.mp4 26.9 MB
  • 07 Unsupervised Learning - Clustering Techniques/009 Hierarchical Clustering Concepts.mp4 25.5 MB
  • 01 Introduction/005 IDE Installation.mp4 23.4 MB
  • 07 Unsupervised Learning - Clustering Techniques/003 K-means Concepts2.mp4 22.3 MB
  • 01 Introduction/001 Course Content.mp4 17.9 MB
  • 08 Hyper Parameter Optimization (Model Tuning)/001 Introduction.mp4 17.9 MB
  • 08 Hyper Parameter Optimization (Model Tuning)/003 K-Means - Model Tuning.mp4 16.0 MB
  • 05 Supervised Learning - Classification/010 Logistic Regression Concepts.mp4 11.4 MB
  • 01 Introduction/004 Python IDE.mp4 7.9 MB
  • 02 Machine Learning Useful Packages (Libraries)/008 Python Source Codes/Chapter6.Regression.py 4.4 kB
  • 02 Machine Learning Useful Packages (Libraries)/008 Python Source Codes/Chapter5.Classification.py 3.4 kB
  • 02 Machine Learning Useful Packages (Libraries)/008 Python Source Codes/Chapter2.Matplotlib.py 3.0 kB
  • 02 Machine Learning Useful Packages (Libraries)/008 Python Source Codes/Chapter3.Preprocessing.py 2.6 kB
  • 02 Machine Learning Useful Packages (Libraries)/008 Python Source Codes/Chapter8.Parameter Tuning.py 2.0 kB
  • 01 Introduction/003 Python Installation.html 1.5 kB
  • 02 Machine Learning Useful Packages (Libraries)/008 Python Source Codes/Chapter7.Clustering.py 1.5 kB
  • 02 Machine Learning Useful Packages (Libraries)/001 Python Source Codes.html 1.3 kB
  • 02 Machine Learning Useful Packages (Libraries)/008 Python Source Codes/Chapter2.Pandas.py 1.1 kB
  • 02 Machine Learning Useful Packages (Libraries)/008 Python Source Codes/Chapter2.NumPy.py 1.1 kB
  • 02 Machine Learning Useful Packages (Libraries)/018 Data_Set.txt 580 Bytes
  • 03 Data Preprocessing/024 Data_Set.txt 580 Bytes
  • 03 Data Preprocessing/033 Data_New.txt 201 Bytes
  • [FreeCourseLab.com].url 126 Bytes
  • 02 Machine Learning Useful Packages (Libraries)/Readme.txt 70 Bytes
  • 03 Data Preprocessing/Readme.txt 70 Bytes

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