GetFreeCourses.Co-Udemy-R for Data Science Your First Step as a Data Scientist

磁力链接/BT种子名称

GetFreeCourses.Co-Udemy-R for Data Science Your First Step as a Data Scientist

磁力链接/BT种子简介

种子哈希：4e377e44e4c0eaba44eafbb65679d5b9dc348c8d
文件大小： 5.39G
已经下载：775次
下载速度：极快
收录时间：2022-04-24
最近下载：2025-09-23

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文件列表

  • 10 Data Science Project - Kaggle Taxi Trip Duration/015 Evaluating - Preparing New Data for Scoring.mp4 148.4 MB
  • 03 Installing Libraries/001 Installing Libraries.mp4 147.6 MB
  • 07 Model Evaluation and Selection/004 Evaluating the Model on Unseen Data.mp4 140.8 MB
  • 07 Model Evaluation and Selection/003 Example of a High Variance Model.mp4 138.6 MB
  • 05 Linear Regression/009 Gradient Descent Intuition - Part 1.mp4 137.1 MB
  • 01 Introduction/001 Welcome to the Course!.mp4 134.7 MB
  • 07 Model Evaluation and Selection/006 Performance across Training and Test Data.mp4 133.9 MB
  • 08 Tree Based Models - Decision Trees/011 Regression Trees - Comparing between Tree and Linear Model.mp4 125.6 MB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/011 Modelling - Training a Random Forest.mp4 118.1 MB
  • 08 Tree Based Models - Decision Trees/002 Classification Trees - First Split and Gini Impurity Concept.mp4 118.0 MB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/007 Feature Engineering - Visualizing Correlation and Adding Features to our table.mp4 116.7 MB
  • 05 Linear Regression/012 Multivariate Linear Regression.mp4 114.8 MB
  • 05 Linear Regression/007 Linear Regression Evaluation.mp4 113.9 MB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/008 Feature Engineering - Creating Weekday feature and Building Data Pipeline.mp4 113.5 MB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/003 Exploratory Data Analysis - Removing Outliers.mp4 111.6 MB
  • 07 Model Evaluation and Selection/007 Regression Metrics - Plotting the Residuals.mp4 109.5 MB
  • 06 Classification Problems and Logistic Regression/005 Log-Loss Function Intuition.mp4 98.5 MB
  • 07 Model Evaluation and Selection/010 Classification Metrics - Fitting Logistic Regression and Confusion Matrix Intro.mp4 94.7 MB
  • 02 Setting up Environment - R and R Studio/002 Installing R Studio.mp4 94.4 MB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/004 Feature Engineering - Time Based Features.mp4 93.5 MB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/009 Modelling - Preparing Data for Modelling.mp4 93.5 MB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/006 Feature Engineering - Building Location Based Features (Manhattan and Euclidean).mp4 93.4 MB
  • 07 Model Evaluation and Selection/002 Example of a High Bias Model.mp4 93.2 MB
  • 09 Tree Based Models - Random Forests/002 Fitting Different Decision Trees.mp4 90.1 MB
  • 08 Tree Based Models - Decision Trees/007 Regression Trees - Intuition.mp4 88.9 MB
  • 05 Linear Regression/010 Gradient Descent Intuition - Part 2.mp4 88.3 MB
  • 07 Model Evaluation and Selection/013 Classification Metrics - Building ROC Curve.mp4 87.0 MB
  • 08 Tree Based Models - Decision Trees/003 Classification Trees - Finding the Best Split with Minimum Gini Impurity.mp4 86.8 MB
  • 05 Linear Regression/008 Linear Regression Closed Form Solution.mp4 86.0 MB
  • 06 Classification Problems and Logistic Regression/002 Classification Problems Intuition - Why Linear Regression is unfit.mp4 85.8 MB
  • 06 Classification Problems and Logistic Regression/007 Visualizing Log-Loss in 3 Dimensions.mp4 83.6 MB
  • 04 Manipulating Data with Dplyr/005 Arrange and Mutate.mp4 78.5 MB
  • 06 Classification Problems and Logistic Regression/006 Gradient Descent Intuition - Classification.mp4 78.1 MB
  • 02 Setting up Environment - R and R Studio/001 Installing R.mp4 77.8 MB
  • 09 Tree Based Models - Random Forests/003 Building a Random Forest from Scratch with Three Estimators.mp4 77.4 MB
  • 07 Model Evaluation and Selection/005 Randomized Train and Test Split.mp4 76.7 MB
  • 05 Linear Regression/011 Visualizing Gradient Descent.mp4 74.4 MB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/010 Modelling - Fitting Linear Regression.mp4 72.8 MB
  • 06 Classification Problems and Logistic Regression/004 Summary of Logistic Regression and Accuracy.mp4 72.7 MB
  • 08 Tree Based Models - Decision Trees/001 Classification Trees - Problem Evaluation and Fitting a Logistic Regression.mp4 72.6 MB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/002 Exploratory Data Analysis - Loading Taxi Trip and Analyzing Outliers.mp4 72.1 MB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/005 Feature Engineering - Visualizing Trip Duration per Feature.mp4 65.6 MB
  • 07 Model Evaluation and Selection/009 Regression Metrics - R-Square Breakdown and MAPE.mp4 65.0 MB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/016 Evaluating - Scoring New Data and Submitting do Kaggle.mp4 64.7 MB
  • 04 Manipulating Data with Dplyr/009 Joining Dataframes.mp4 64.7 MB
  • 07 Model Evaluation and Selection/008 Regression Metrics - MSE, MAE and RMSE.mp4 64.3 MB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/012 Modelling - Caret Implementation and API.mp4 63.1 MB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/013 Modelling - Building Custom Experiments _ Hyperparameter Tuning.mp4 59.7 MB
  • 06 Classification Problems and Logistic Regression/003 Calculating Sigmoid Function and Fitting a Logistic Regression.mp4 59.1 MB
  • 08 Tree Based Models - Decision Trees/009 Regression Trees - Finding the Best Split with Residual Sum of Squares.mp4 57.6 MB
  • 08 Tree Based Models - Decision Trees/010 Regression Trees - Fitting the Algorithm.mp4 54.6 MB
  • 04 Manipulating Data with Dplyr/002 Filter and Pipe Format.mp4 54.2 MB
  • 09 Tree Based Models - Random Forests/001 Random Forest Intuition and Subsetting Data.mp4 51.7 MB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/014 Modelling - Evaluating Best Model.mp4 51.6 MB
  • 09 Tree Based Models - Random Forests/005 Random Forest - R Package Implementation.mp4 50.5 MB
  • 07 Model Evaluation and Selection/014 Classification Metrics - ROCR Package and Area Under the Curve.mp4 47.9 MB
  • 08 Tree Based Models - Decision Trees/005 Classification Trees - Adding more Thresholds and Visualizing Classification.mp4 47.6 MB
  • 08 Tree Based Models - Decision Trees/004 Classification Trees - Fitting a Decision Tree using RPart.mp4 45.5 MB
  • 07 Model Evaluation and Selection/012 Classification Metrics - Precision, Recall and F-Score.mp4 42.7 MB
  • 05 Linear Regression/006 Training our First Linear Model.mp4 42.1 MB
  • 05 Linear Regression/004 Fitting a Random Line.mp4 41.5 MB
  • 04 Manipulating Data with Dplyr/001 Intro to Dplyr and Tibble Data Structure.mp4 40.7 MB
  • 08 Tree Based Models - Decision Trees/008 Regression Trees - Calculating Residual Sum of Squares.mp4 40.4 MB
  • 04 Manipulating Data with Dplyr/006 Select and Distinct.mp4 38.8 MB
  • 08 Tree Based Models - Decision Trees/006 Classification Trees - Tweaking Hyperparameters and Checking Accuracy.mp4 37.9 MB
  • 09 Tree Based Models - Random Forests/004 Measuring the Accuracy of Each Trees and of the Ensemble Average.mp4 37.3 MB
  • 05 Linear Regression/003 Plotting Feature (Age) and Target (Income) Variables.mp4 36.0 MB
  • 05 Linear Regression/002 Loading the Data into R.mp4 34.6 MB
  • 04 Manipulating Data with Dplyr/003 Glimpse and Lists as Columns.mp4 34.6 MB
  • 04 Manipulating Data with Dplyr/007 Sample_N and Sample_Frac.mp4 31.9 MB
  • 05 Linear Regression/005 Adjusting the Weight of our Linear Model.mp4 31.3 MB
  • 04 Manipulating Data with Dplyr/008 Summarize and Group By.mp4 31.3 MB
  • 07 Model Evaluation and Selection/011 Classification Metrics - TP, FP, TN, FN.mp4 29.2 MB
  • 04 Manipulating Data with Dplyr/004 Function Encapsulation and Multiple Arguments.mp4 29.1 MB
  • 03 Installing Libraries/002 Loading Libraries.mp4 28.4 MB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/001 Data Science Project - Taxi Trip Duration Project - Introduction.mp4 22.1 MB
  • 11 Thank you!/003 Final Notes.mp4 14.5 MB
  • 05 Linear Regression/001 Linear Regression - Introduction.mp4 13.4 MB
  • 06 Classification Problems and Logistic Regression/001 Classification Problems - Introduction.mp4 10.6 MB
  • 07 Model Evaluation and Selection/001 Model Evaluation and Selection - Introduction.mp4 8.2 MB
  • 03 Installing Libraries/003 Let's start!.mp4 7.2 MB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/015 Evaluating - Preparing New Data for Scoring.en.srt 24.2 kB
  • 07 Model Evaluation and Selection/006 Performance across Training and Test Data.en.srt 21.2 kB
  • 05 Linear Regression/009 Gradient Descent Intuition - Part 1.en.srt 21.2 kB
  • 07 Model Evaluation and Selection/004 Evaluating the Model on Unseen Data.en.srt 20.0 kB
  • 06 Classification Problems and Logistic Regression/005 Log-Loss Function Intuition.en.srt 19.9 kB
  • 05 Linear Regression/012 Multivariate Linear Regression.en.srt 19.9 kB
  • 07 Model Evaluation and Selection/003 Example of a High Variance Model.en.srt 19.3 kB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/011 Modelling - Training a Random Forest.en.srt 18.9 kB
  • 08 Tree Based Models - Decision Trees/002 Classification Trees - First Split and Gini Impurity Concept.en.srt 18.6 kB
  • 05 Linear Regression/007 Linear Regression Evaluation.en.srt 18.4 kB
  • 07 Model Evaluation and Selection/007 Regression Metrics - Plotting the Residuals.en.srt 18.3 kB
  • 01 Introduction/001 Welcome to the Course!.en.srt 18.0 kB
  • 08 Tree Based Models - Decision Trees/011 Regression Trees - Comparing between Tree and Linear Model.en.srt 18.0 kB
  • 05 Linear Regression/008 Linear Regression Closed Form Solution.en.srt 17.8 kB
  • 07 Model Evaluation and Selection/005 Randomized Train and Test Split.en.srt 17.2 kB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/008 Feature Engineering - Creating Weekday feature and Building Data Pipeline.en.srt 17.1 kB
  • 07 Model Evaluation and Selection/010 Classification Metrics - Fitting Logistic Regression and Confusion Matrix Intro.en.srt 17.0 kB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/004 Feature Engineering - Time Based Features.en.srt 16.1 kB
  • 06 Classification Problems and Logistic Regression/002 Classification Problems Intuition - Why Linear Regression is unfit.en.srt 16.0 kB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/007 Feature Engineering - Visualizing Correlation and Adding Features to our table.en.srt 15.9 kB
  • 08 Tree Based Models - Decision Trees/007 Regression Trees - Intuition.en.srt 15.8 kB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/003 Exploratory Data Analysis - Removing Outliers.en.srt 15.8 kB
  • 07 Model Evaluation and Selection/002 Example of a High Bias Model.en.srt 15.5 kB
  • 07 Model Evaluation and Selection/013 Classification Metrics - Building ROC Curve.en.srt 14.6 kB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/009 Modelling - Preparing Data for Modelling.en.srt 14.5 kB
  • 03 Installing Libraries/001 Installing Libraries.en.srt 14.4 kB
  • 06 Classification Problems and Logistic Regression/007 Visualizing Log-Loss in 3 Dimensions.en.srt 13.6 kB
  • 09 Tree Based Models - Random Forests/002 Fitting Different Decision Trees.en.srt 13.1 kB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/006 Feature Engineering - Building Location Based Features (Manhattan and Euclidean).en.srt 13.0 kB
  • 05 Linear Regression/010 Gradient Descent Intuition - Part 2.en.srt 13.0 kB
  • 05 Linear Regression/011 Visualizing Gradient Descent.en.srt 12.9 kB
  • 08 Tree Based Models - Decision Trees/001 Classification Trees - Problem Evaluation and Fitting a Logistic Regression.en.srt 12.8 kB
  • 06 Classification Problems and Logistic Regression/006 Gradient Descent Intuition - Classification.en.srt 12.8 kB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/002 Exploratory Data Analysis - Loading Taxi Trip and Analyzing Outliers.en.srt 12.3 kB
  • 08 Tree Based Models - Decision Trees/003 Classification Trees - Finding the Best Split with Minimum Gini Impurity.en.srt 11.9 kB
  • 06 Classification Problems and Logistic Regression/004 Summary of Logistic Regression and Accuracy.en.srt 11.2 kB
  • 09 Tree Based Models - Random Forests/003 Building a Random Forest from Scratch with Three Estimators.en.srt 11.1 kB
  • 02 Setting up Environment - R and R Studio/002 Installing R Studio.en.srt 11.1 kB
  • 07 Model Evaluation and Selection/009 Regression Metrics - R-Square Breakdown and MAPE.en.srt 10.9 kB
  • 09 Tree Based Models - Random Forests/001 Random Forest Intuition and Subsetting Data.en.srt 10.7 kB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/010 Modelling - Fitting Linear Regression.en.srt 10.6 kB
  • 07 Model Evaluation and Selection/008 Regression Metrics - MSE, MAE and RMSE.en.srt 10.4 kB
  • 04 Manipulating Data with Dplyr/005 Arrange and Mutate.en.srt 10.2 kB
  • 06 Classification Problems and Logistic Regression/003 Calculating Sigmoid Function and Fitting a Logistic Regression.en.srt 10.2 kB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/016 Evaluating - Scoring New Data and Submitting do Kaggle.en.srt 10.1 kB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/012 Modelling - Caret Implementation and API.en.srt 9.5 kB
  • 07 Model Evaluation and Selection/014 Classification Metrics - ROCR Package and Area Under the Curve.en.srt 9.4 kB
  • 04 Manipulating Data with Dplyr/002 Filter and Pipe Format.en.srt 9.2 kB
  • 02 Setting up Environment - R and R Studio/001 Installing R.en.srt 9.1 kB
  • 04 Manipulating Data with Dplyr/009 Joining Dataframes.en.srt 9.0 kB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/005 Feature Engineering - Visualizing Trip Duration per Feature.en.srt 8.9 kB
  • 08 Tree Based Models - Decision Trees/010 Regression Trees - Fitting the Algorithm.en.srt 8.7 kB
  • 09 Tree Based Models - Random Forests/005 Random Forest - R Package Implementation.en.srt 8.6 kB
  • 07 Model Evaluation and Selection/012 Classification Metrics - Precision, Recall and F-Score.en.srt 8.4 kB
  • 08 Tree Based Models - Decision Trees/005 Classification Trees - Adding more Thresholds and Visualizing Classification.en.srt 8.2 kB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/013 Modelling - Building Custom Experiments _ Hyperparameter Tuning.en.srt 8.1 kB
  • 08 Tree Based Models - Decision Trees/009 Regression Trees - Finding the Best Split with Residual Sum of Squares.en.srt 8.0 kB
  • 04 Manipulating Data with Dplyr/001 Intro to Dplyr and Tibble Data Structure.en.srt 8.0 kB
  • 08 Tree Based Models - Decision Trees/004 Classification Trees - Fitting a Decision Tree using RPart.en.srt 7.7 kB
  • 05 Linear Regression/006 Training our First Linear Model.en.srt 7.0 kB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/014 Modelling - Evaluating Best Model.en.srt 6.9 kB
  • 05 Linear Regression/004 Fitting a Random Line.en.srt 6.9 kB
  • 04 Manipulating Data with Dplyr/006 Select and Distinct.en.srt 6.5 kB
  • 08 Tree Based Models - Decision Trees/008 Regression Trees - Calculating Residual Sum of Squares.en.srt 6.4 kB
  • 08 Tree Based Models - Decision Trees/006 Classification Trees - Tweaking Hyperparameters and Checking Accuracy.en.srt 6.3 kB
  • 05 Linear Regression/002 Loading the Data into R.en.srt 5.8 kB
  • 05 Linear Regression/003 Plotting Feature (Age) and Target (Income) Variables.en.srt 5.8 kB
  • 10 Data Science Project - Kaggle Taxi Trip Duration/001 Data Science Project - Taxi Trip Duration Project - Introduction.en.srt 5.8 kB
  • 05 Linear Regression/005 Adjusting the Weight of our Linear Model.en.srt 5.0 kB
  • 07 Model Evaluation and Selection/011 Classification Metrics - TP, FP, TN, FN.en.srt 4.9 kB
  • 09 Tree Based Models - Random Forests/004 Measuring the Accuracy of Each Trees and of the Ensemble Average.en.srt 4.8 kB
  • 04 Manipulating Data with Dplyr/003 Glimpse and Lists as Columns.en.srt 4.8 kB
  • 04 Manipulating Data with Dplyr/008 Summarize and Group By.en.srt 4.6 kB
  • 04 Manipulating Data with Dplyr/004 Function Encapsulation and Multiple Arguments.en.srt 4.5 kB
  • 04 Manipulating Data with Dplyr/007 Sample_N and Sample_Frac.en.srt 4.3 kB
  • 07 Model Evaluation and Selection/001 Model Evaluation and Selection - Introduction.en.srt 3.2 kB
  • 03 Installing Libraries/002 Loading Libraries.en.srt 2.8 kB
  • 06 Classification Problems and Logistic Regression/001 Classification Problems - Introduction.en.srt 2.8 kB
  • 11 Thank you!/003 Final Notes.en.srt 1.9 kB
  • 05 Linear Regression/001 Linear Regression - Introduction.en.srt 1.8 kB
  • 11 Thank you!/001 Bonus Lecture - Other Courses.html 1.8 kB
  • 01 Introduction/002 Course Materials.html 1.4 kB
  • 11 Thank you!/002 Detailed Feedback.html 1.2 kB
  • 04 Manipulating Data with Dplyr/010 Small Typo.html 1.1 kB
  • 03 Installing Libraries/003 Let's start!.en.srt 995 Bytes
  • 01 Introduction/external-assets-links.txt 231 Bytes
  • 04 Manipulating Data with Dplyr/How you can help GetFreeCourses.Co.txt 182 Bytes
  • 10 Data Science Project - Kaggle Taxi Trip Duration/How you can help GetFreeCourses.Co.txt 182 Bytes
  • How you can help GetFreeCourses.Co.txt 182 Bytes
  • 02 Setting up Environment - R and R Studio/external-assets-links.txt 120 Bytes
  • 04 Manipulating Data with Dplyr/GetFreeCourses.Co.url 116 Bytes
  • 10 Data Science Project - Kaggle Taxi Trip Duration/GetFreeCourses.Co.url 116 Bytes
  • Download Paid Udemy Courses For Free.url 116 Bytes
  • GetFreeCourses.Co.url 116 Bytes

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本站不存储任何资源内容，只收集BT种子元数据(例如文件名和文件大小)和磁力链接(BT种子标识符)，并提供查询服务，是一个完全合法的搜索引擎系统。 网站不提供种子下载服务，用户可以通过第三方链接或磁力链接获取到相关的种子资源。本站也不对BT种子真实性及合法性负责，请用户注意甄别！