[FreeCourseSite.com] Udemy - Machine Learning & Deep Learning in Python & R - 2048BT - 全球最新最全bt种子资源在线搜索库，实时索引全球磁力链接资源

BT种子名称

分享给好友

BT种子基本信息

种子哈希：0d08561ced314dc917703837fcd2711631dd834b
文档大小：14.1 GB
文档个数：286个文档
下载次数：1680次
下载速度：极快
收录时间：2021-11-16
最近下载：2024-08-16
DMCA/屏蔽：DMCA/屏蔽

下载磁力链接

magnet:?xt=urn:btih:0D08561CED314DC917703837FCD2711631DD834B
复制磁力链接到utorrent、Bitcomet、迅雷、115、百度网盘、PIKPAK等下载工具进行下载。

下载BT种子

磁力链接种子下载迅雷下载二维码含羞草 51品茶 91视频逼哩逼哩欲漫涩草榴社区抖阴破解版成人快手暗网禁区缅北禁地 TikTok成人版暗网解密

[FreeCourseSite.com] Udemy - Machine Learning & Deep Learning in Python & R的二维码

文档列表

27 ANN in R/008 Saving - Restoring Models and Using Callbacks.mp4 226.5 MB
37 Time Series - Preprocessing in Python/003 Time Series - Visualization in Python.mp4 173.2 MB
18 Ensemble technique 3 - Boosting/007 XGBoosting in R.mp4 169.1 MB
26 ANN in Python/009 Building Neural Network for Regression Problem.mp4 163.5 MB
26 ANN in Python/011 Saving - Restoring Models and Using Callbacks.mp4 158.9 MB
23 Creating Support Vector Machine Model in R/004 Classification SVM model using Linear Kernel.mp4 145.9 MB
27 ANN in R/006 Building Regression Model with Functional API.mp4 137.5 MB
27 ANN in R/003 Building,Compiling and Training.mp4 137.1 MB
34 Transfer Learning _ Basics/006 Project - Transfer Learning - VGG16.mp4 135.4 MB
07 Linear Regression/020 Ridge regression and Lasso in Python.mp4 135.1 MB
25 Neural Networks - Stacking cells to create network/003 Back Propagation.mp4 128.1 MB
38 Time Series - Important Concepts/005 Differencing in Python.mp4 118.5 MB
37 Time Series - Preprocessing in Python/005 Time Series - Feature Engineering in Python.mp4 118.2 MB
27 ANN in R/002 Data Normalization and Test-Train Split.mp4 117.2 MB
05 Introduction to Machine Learning/001 Introduction to Machine Learning.mp4 114.5 MB
37 Time Series - Preprocessing in Python/001 Data Loading in Python.mp4 114.1 MB
23 Creating Support Vector Machine Model in R/008 SVM based Regression Model in R.mp4 111.3 MB
07 Linear Regression/021 Ridge regression and Lasso in R.mp4 108.5 MB
14 Simple Decision Trees/013 Building a Regression Tree in R.mp4 108.3 MB
35 Transfer Learning in R/001 Project - Transfer Learning - VGG16 (Implementation).mp4 106.5 MB
37 Time Series - Preprocessing in Python/007 Time Series - Upsampling and Downsampling in Python.mp4 105.6 MB
06 Data Preprocessing/016 Bi-variate analysis and Variable transformation.mp4 105.3 MB
27 ANN in R/004 Evaluating and Predicting.mp4 104.1 MB
06 Data Preprocessing/008 EDD in R.mp4 101.7 MB
03 Setting up R Studio and R crash course/007 Creating Barplots in R.mp4 101.4 MB
07 Linear Regression/003 Assessing accuracy of predicted coefficients.mp4 96.6 MB
26 ANN in Python/010 Using Functional API for complex architectures.mp4 96.6 MB
18 Ensemble technique 3 - Boosting/005 AdaBoosting in R.mp4 93.0 MB
32 Project _ Creating CNN model from scratch/001 Project in R - Data Preprocessing.mp4 92.0 MB
24 Introduction - Deep Learning/004 Python - Creating Perceptron model.mp4 90.8 MB
15 Simple Classification Tree/005 Building a classification Tree in R.mp4 89.2 MB
27 ANN in R/005 ANN with NeuralNets Package.mp4 88.5 MB
23 Creating Support Vector Machine Model in R/006 Polynomial Kernel with Hyperparameter Tuning.mp4 87.2 MB
06 Data Preprocessing/025 Correlation Matrix in R.mp4 87.2 MB
03 Setting up R Studio and R crash course/003 Packages in R.mp4 87.0 MB
15 Simple Classification Tree/004 Classification tree in Python _ Training.mp4 86.7 MB
14 Simple Decision Trees/018 Pruning a Tree in R.mp4 86.1 MB
26 ANN in Python/007 Compiling and Training the Neural Network model.mp4 85.6 MB
17 Ensemble technique 2 - Random Forests/003 Using Grid Search in Python.mp4 84.6 MB
27 ANN in R/007 Complex Architectures using Functional API.mp4 83.4 MB
26 ANN in Python/006 Building the Neural Network using Keras.mp4 83.0 MB
07 Linear Regression/017 Subset selection techniques.mp4 82.9 MB
08 Classification Models_ Data Preparation/001 The Data and the Data Dictionary.mp4 82.8 MB
08 Classification Models_ Data Preparation/004 EDD in Python.mp4 81.4 MB
16 Ensemble technique 1 - Bagging/002 Ensemble technique 1 - Bagging in Python.mp4 81.1 MB
07 Linear Regression/015 Test-Train Split in R.mp4 79.3 MB
12 K-Nearest Neighbors classifier/004 K-Nearest Neighbors classifier.mp4 79.1 MB
18 Ensemble technique 3 - Boosting/006 Ensemble technique 3c - XGBoost in Python.mp4 78.6 MB
40 Time Series - ARIMA model/003 ARIMA model in Python.mp4 78.0 MB
11 Linear Discriminant Analysis (LDA)/003 Linear Discriminant Analysis in R.mp4 78.0 MB
12 K-Nearest Neighbors classifier/003 Test-Train Split in R.mp4 77.8 MB
14 Simple Decision Trees/017 Pruning a tree in Python.mp4 77.1 MB
31 Project _ Creating CNN model from scratch in Python/003 Project - Data Preprocessing in Python.mp4 75.3 MB
30 Creating CNN model in R/003 Creating Model Architecture.mp4 75.1 MB
06 Data Preprocessing/023 Correlation Analysis.mp4 75.1 MB
06 Data Preprocessing/010 Outlier Treatment in Python.mp4 73.7 MB
26 ANN in Python/008 Evaluating performance and Predicting using Keras.mp4 73.3 MB
07 Linear Regression/010 Multiple Linear Regression in Python.mp4 73.1 MB
06 Data Preprocessing/003 The Dataset and the Data Dictionary.mp4 72.6 MB
18 Ensemble technique 3 - Boosting/003 Gradient Boosting in R.mp4 72.4 MB
30 Creating CNN model in R/005 Model Performance.mp4 71.4 MB
28 CNN - Basics/005 Channels.mp4 71.1 MB
22 Creating Support Vector Machine Model in Python/007 SVM based Regression Model in Python.mp4 70.9 MB
30 Creating CNN model in R/002 Data Preprocessing.mp4 70.3 MB
08 Classification Models_ Data Preparation/005 EDD in R.mp4 69.7 MB
41 Time Series - SARIMA model/002 SARIMA model in Python.mp4 69.4 MB
31 Project _ Creating CNN model from scratch in Python/004 Project - Training CNN model in Python.mp4 69.2 MB
04 Basics of Statistics/003 Describing data Graphically.mp4 68.6 MB
02 Setting up Python and Jupyter Notebook/003 Opening Jupyter Notebook.mp4 68.4 MB
12 K-Nearest Neighbors classifier/007 K-Nearest Neighbors in R.mp4 68.0 MB
02 Setting up Python and Jupyter Notebook/006 Strings in Python_ Python Basics.mp4 67.6 MB
22 Creating Support Vector Machine Model in Python/011 SVM Based classification model.mp4 67.2 MB
35 Transfer Learning in R/002 Project - Transfer Learning - VGG16 (Performance).mp4 67.2 MB
37 Time Series - Preprocessing in Python/002 Time Series - Visualization Basics.mp4 66.8 MB
07 Linear Regression/018 Subset selection in R.mp4 66.6 MB
07 Linear Regression/005 Simple Linear Regression in Python.mp4 66.5 MB
36 Time Series Analysis and Forecasting/005 Time Series - Basic Notations.mp4 65.5 MB
07 Linear Regression/011 Multiple Linear Regression in R.mp4 65.4 MB
25 Neural Networks - Stacking cells to create network/004 Some Important Concepts.mp4 65.2 MB
06 Data Preprocessing/007 EDD in Python.mp4 64.8 MB
26 ANN in Python/012 Hyperparameter Tuning.mp4 63.6 MB
23 Creating Support Vector Machine Model in R/005 Hyperparameter Tuning for Linear Kernel.mp4 63.4 MB
25 Neural Networks - Stacking cells to create network/002 Gradient Descent.mp4 63.3 MB
02 Setting up Python and Jupyter Notebook/007 Lists, Tuples and Directories_ Python Basics.mp4 63.2 MB
03 Setting up R Studio and R crash course/006 Inputting data part 3_ Importing from CSV or Text files.mp4 63.0 MB
38 Time Series - Important Concepts/003 Decomposing Time Series in Python.mp4 62.7 MB
37 Time Series - Preprocessing in Python/004 Time Series - Feature Engineering Basics.mp4 62.4 MB
16 Ensemble technique 1 - Bagging/003 Bagging in R.mp4 61.8 MB
29 Creating CNN model in Python/004 Comparison - Pooling vs Without Pooling in Python.mp4 60.8 MB
22 Creating Support Vector Machine Model in Python/012 Hyper Parameter Tuning.mp4 60.5 MB
39 Time Series - Implementation in Python/001 Test Train Split in Python.mp4 60.2 MB
23 Creating Support Vector Machine Model in R/007 Radial Kernel with Hyperparameter Tuning.mp4 59.4 MB
39 Time Series - Implementation in Python/007 Moving Average model in Python.mp4 59.4 MB
32 Project _ Creating CNN model from scratch/005 Project in R - Data Augmentation.mp4 59.1 MB
26 ANN in Python/003 Dataset for classification.mp4 58.9 MB
20 Support Vector Classifier/001 Support Vector classifiers.mp4 58.9 MB
07 Linear Regression/008 The F - statistic.mp4 58.7 MB
10 Logistic Regression/012 Predicting probabilities, assigning classes and making Confusion Matrix in R.mp4 58.4 MB
06 Data Preprocessing/018 Variable transformation in R.mp4 58.1 MB
06 Data Preprocessing/024 Correlation Analysis in Python.mp4 58.0 MB
29 Creating CNN model in Python/003 CNN model in Python - Training and results.mp4 57.8 MB
23 Creating Support Vector Machine Model in R/001 Importing Data into R.mp4 56.3 MB
39 Time Series - Implementation in Python/004 Auto Regression Model creation in Python.mp4 56.1 MB
33 Project _ Data Augmentation for avoiding overfitting/002 Project - Data Augmentation Training and Results.mp4 55.6 MB
28 CNN - Basics/004 Filters and Feature maps.mp4 55.3 MB
10 Logistic Regression/009 Creating Confusion Matrix in Python.mp4 53.7 MB
28 CNN - Basics/001 CNN Introduction.mp4 53.6 MB
23 Creating Support Vector Machine Model in R/002 Test-Train Split.mp4 52.9 MB
39 Time Series - Implementation in Python/005 Auto Regression with Walk Forward validation in Python.mp4 52.0 MB
31 Project _ Creating CNN model from scratch in Python/001 Project - Introduction.mp4 51.8 MB
10 Logistic Regression/002 Training a Simple Logistic Model in Python.mp4 50.2 MB
08 Classification Models_ Data Preparation/006 Outlier treatment in Python.mp4 49.6 MB
02 Setting up Python and Jupyter Notebook/009 Working with Pandas Library of Python.mp4 49.2 MB
28 CNN - Basics/006 PoolingLayer.mp4 49.1 MB
17 Ensemble technique 2 - Random Forests/002 Ensemble technique 2 - Random Forests in Python.mp4 49.0 MB
32 Project _ Creating CNN model from scratch/002 CNN Project in R - Structure and Compile.mp4 48.3 MB
15 Simple Classification Tree/003 Classification tree in Python _ Preprocessing.mp4 47.6 MB
22 Creating Support Vector Machine Model in Python/009 Classification model - Preprocessing.mp4 47.6 MB
25 Neural Networks - Stacking cells to create network/005 Hyperparameter.mp4 47.6 MB
07 Linear Regression/014 Test train split in Python.mp4 47.1 MB
24 Introduction - Deep Learning/002 Perceptron.mp4 46.9 MB
30 Creating CNN model in R/006 Comparison - Pooling vs Without Pooling in R.mp4 46.8 MB
08 Classification Models_ Data Preparation/013 Dummy variable creation in R.mp4 46.5 MB
26 ANN in Python/004 Normalization and Test-Train split.mp4 46.3 MB
06 Data Preprocessing/017 Variable transformation and deletion in Python.mp4 46.3 MB
06 Data Preprocessing/022 Dummy variable creation in R.mp4 46.1 MB
14 Simple Decision Trees/011 Splitting Data into Test and Train Set in R.mp4 46.1 MB
02 Setting up Python and Jupyter Notebook/008 Working with Numpy Library of Python.mp4 46.0 MB
14 Simple Decision Trees/002 Understanding a Regression Tree.mp4 45.8 MB
14 Simple Decision Trees/006 Importing the Data set into R.mp4 45.8 MB
07 Linear Regression/004 Assessing Model Accuracy_ RSE and R squared.mp4 45.7 MB
07 Linear Regression/002 Basic Equations and Ordinary Least Squares (OLS) method.mp4 45.5 MB
39 Time Series - Implementation in Python/002 Naive (Persistence) model in Python.mp4 45.5 MB
29 Creating CNN model in Python/002 CNN model in Python - structure and Compile.mp4 45.3 MB
14 Simple Decision Trees/001 Basics of Decision Trees.mp4 44.7 MB
12 K-Nearest Neighbors classifier/006 K-Nearest Neighbors in Python_ Part 2.mp4 44.4 MB
03 Setting up R Studio and R crash course/008 Creating Histograms in R.mp4 44.1 MB
07 Linear Regression/012 Test-train split.mp4 43.9 MB
13 Comparing results from 3 models/001 Understanding the results of classification models.mp4 43.7 MB
33 Project _ Data Augmentation for avoiding overfitting/001 Project - Data Augmentation Preprocessing.mp4 43.4 MB
40 Time Series - ARIMA model/001 ACF and PACF.mp4 43.2 MB
11 Linear Discriminant Analysis (LDA)/001 Linear Discriminant Analysis.mp4 42.9 MB
02 Setting up Python and Jupyter Notebook/004 Introduction to Jupyter.mp4 42.9 MB
07 Linear Regression/006 Simple Linear Regression in R.mp4 42.8 MB
03 Setting up R Studio and R crash course/004 Inputting data part 1_ Inbuilt datasets of R.mp4 42.7 MB
29 Creating CNN model in Python/001 CNN model in Python - Preprocessing.mp4 42.6 MB
25 Neural Networks - Stacking cells to create network/001 Basic Terminologies.mp4 42.4 MB
02 Setting up Python and Jupyter Notebook/010 Working with Seaborn Library of Python.mp4 42.3 MB
21 Support Vector Machines/001 Kernel Based Support Vector Machines.mp4 42.1 MB
18 Ensemble technique 3 - Boosting/002 Ensemble technique 3a - Boosting in Python.mp4 41.8 MB
05 Introduction to Machine Learning/002 Building a Machine Learning Model.mp4 41.4 MB
12 K-Nearest Neighbors classifier/001 Test-Train Split.mp4 41.2 MB
41 Time Series - SARIMA model/001 SARIMA model.mp4 40.9 MB
03 Setting up R Studio and R crash course/002 Basics of R and R studio.mp4 40.7 MB
37 Time Series - Preprocessing in Python/009 Moving Average.mp4 40.6 MB
04 Basics of Statistics/004 Measures of Centers.mp4 40.4 MB
22 Creating Support Vector Machine Model in Python/006 Standardizing the data.mp4 40.3 MB
08 Classification Models_ Data Preparation/011 Variable transformation in R.mp4 39.9 MB
14 Simple Decision Trees/004 The Data set for this part.mp4 39.1 MB
12 K-Nearest Neighbors classifier/005 K-Nearest Neighbors in Python_ Part 1.mp4 39.0 MB
22 Creating Support Vector Machine Model in Python/014 Radial Kernel with Hyperparameter Tuning.mp4 39.0 MB
22 Creating Support Vector Machine Model in Python/002 The Data set for the Regression problem.mp4 39.0 MB
06 Data Preprocessing/020 Dummy variable creation_ Handling qualitative data.mp4 38.6 MB
03 Setting up R Studio and R crash course/001 Installing R and R studio.mp4 37.4 MB
10 Logistic Regression/010 Evaluating performance of model.mp4 36.9 MB
24 Introduction - Deep Learning/003 Activation Functions.mp4 36.3 MB
36 Time Series Analysis and Forecasting/004 Forecasting model creation - Steps 1 (Goal).mp4 36.2 MB
07 Linear Regression/007 Multiple Linear Regression.mp4 36.0 MB
07 Linear Regression/019 Shrinkage methods_ Ridge and Lasso.mp4 35.0 MB
12 K-Nearest Neighbors classifier/002 Test-Train Split in Python.mp4 34.7 MB
10 Logistic Regression/001 Logistic Regression.mp4 34.5 MB
38 Time Series - Important Concepts/004 Differencing.mp4 33.9 MB
30 Creating CNN model in R/004 Compiling and training.mp4 33.8 MB
40 Time Series - ARIMA model/004 ARIMA model with Walk Forward Validation in Python.mp4 33.7 MB
28 CNN - Basics/003 Padding.mp4 33.2 MB
06 Data Preprocessing/011 Outlier Treatment in R.mp4 32.2 MB
17 Ensemble technique 2 - Random Forests/004 Random Forest in R.mp4 32.2 MB
18 Ensemble technique 3 - Boosting/001 Boosting.mp4 32.1 MB
18 Ensemble technique 3 - Boosting/004 Ensemble technique 3b - AdaBoost in Python.mp4 32.0 MB
34 Transfer Learning _ Basics/005 Transfer Learning.mp4 31.4 MB
19 Maximum Margin Classifier/002 The Concept of a Hyperplane.mp4 30.8 MB
01 Introduction/001 Introduction.mp4 30.8 MB
08 Classification Models_ Data Preparation/010 Variable transformation and Deletion in Python.mp4 30.7 MB
24 Introduction - Deep Learning/001 Introduction to Neural Networks and Course flow.mp4 30.5 MB
15 Simple Classification Tree/001 Classification tree.mp4 29.6 MB
16 Ensemble technique 1 - Bagging/001 Ensemble technique 1 - Bagging.mp4 29.5 MB
06 Data Preprocessing/004 Importing Data in Python.mp4 29.2 MB
10 Logistic Regression/004 Result of Simple Logistic Regression.mp4 28.2 MB
06 Data Preprocessing/021 Dummy variable creation in Python.mp4 27.8 MB
08 Classification Models_ Data Preparation/012 Dummy variable creation in Python.mp4 27.6 MB
10 Logistic Regression/006 Training multiple predictor Logistic model in Python.mp4 27.5 MB
06 Data Preprocessing/014 Missing Value imputation in R.mp4 27.3 MB
36 Time Series Analysis and Forecasting/002 Time Series Forecasting - Use cases.mp4 27.2 MB
14 Simple Decision Trees/005 Importing the Data set into Python.mp4 27.1 MB
22 Creating Support Vector Machine Model in Python/003 Importing data for regression model.mp4 27.1 MB
10 Logistic Regression/003 Training a Simple Logistic model in R.mp4 26.8 MB
03 Setting up R Studio and R crash course/005 Inputting data part 2_ Manual data entry.mp4 26.8 MB
08 Classification Models_ Data Preparation/007 Outlier Treatment in R.mp4 26.6 MB
07 Linear Regression/013 Bias Variance trade-off.mp4 26.3 MB
06 Data Preprocessing/012 Missing Value Imputation.mp4 26.2 MB
14 Simple Decision Trees/008 Dummy Variable creation in Python.mp4 26.2 MB
14 Simple Decision Trees/010 Test-Train split in Python.mp4 26.1 MB
22 Creating Support Vector Machine Model in Python/005 Test-Train Split.mp4 26.1 MB
32 Project _ Creating CNN model from scratch/003 Project in R - Training.mp4 25.8 MB
06 Data Preprocessing/009 Outlier Treatment.mp4 25.7 MB
06 Data Preprocessing/006 Univariate analysis and EDD.mp4 25.4 MB
39 Time Series - Implementation in Python/006 Moving Average model -Basics.mp4 25.3 MB
32 Project _ Creating CNN model from scratch/006 Project in R - Validation Performance.mp4 24.8 MB
06 Data Preprocessing/013 Missing Value Imputation in Python.mp4 24.6 MB
32 Project _ Creating CNN model from scratch/004 Project in R - Model Performance.mp4 24.3 MB
22 Creating Support Vector Machine Model in Python/013 Polynomial Kernel with Hyperparameter Tuning.mp4 24.0 MB
04 Basics of Statistics/005 Measures of Dispersion.mp4 24.0 MB
27 ANN in R/001 Installing Keras and Tensorflow.mp4 23.9 MB
08 Classification Models_ Data Preparation/008 Missing Value Imputation in Python.mp4 23.7 MB
07 Linear Regression/009 Interpreting results of Categorical variables.mp4 23.6 MB
19 Maximum Margin Classifier/003 Maximum Margin Classifier.mp4 23.6 MB
06 Data Preprocessing/001 Gathering Business Knowledge.mp4 23.4 MB
13 Comparing results from 3 models/002 Summary of the three models.mp4 23.3 MB
08 Classification Models_ Data Preparation/002 Data Import in Python.mp4 23.1 MB
04 Basics of Statistics/001 Types of Data.mp4 22.8 MB
14 Simple Decision Trees/015 Plotting decision tree in Python.mp4 22.5 MB
34 Transfer Learning _ Basics/004 GoogLeNet.mp4 22.4 MB
40 Time Series - ARIMA model/002 ARIMA model - Basics.mp4 22.4 MB
38 Time Series - Important Concepts/002 Random Walk.mp4 22.2 MB
10 Logistic Regression/008 Confusion Matrix.mp4 22.1 MB
31 Project _ Creating CNN model from scratch in Python/005 Project in Python - model results.mp4 22.0 MB
34 Transfer Learning _ Basics/001 ILSVRC.mp4 21.9 MB
02 Setting up Python and Jupyter Notebook/002 This is a milestone!.mp4 21.7 MB
06 Data Preprocessing/002 Data Exploration.mp4 21.5 MB
09 The Three classification models/001 Three Classifiers and the problem statement.mp4 21.3 MB
06 Data Preprocessing/019 Non-usable variables.mp4 21.2 MB
26 ANN in Python/002 Installing Tensorflow and Keras.mp4 21.0 MB
08 Classification Models_ Data Preparation/009 Missing Value imputation in R.mp4 20.0 MB
15 Simple Classification Tree/002 The Data set for Classification problem.mp4 19.5 MB
22 Creating Support Vector Machine Model in Python/008 The Data set for the Classification problem.mp4 19.4 MB
14 Simple Decision Trees/016 Pruning a tree.mp4 19.4 MB
17 Ensemble technique 2 - Random Forests/001 Ensemble technique 2 - Random Forests.mp4 19.1 MB
14 Simple Decision Trees/007 Missing value treatment in Python.mp4 18.8 MB
14 Simple Decision Trees/012 Creating Decision tree in Python.mp4 18.7 MB
06 Data Preprocessing/015 Seasonality in Data.mp4 17.8 MB
37 Time Series - Preprocessing in Python/006 Time Series - Upsampling and Downsampling.mp4 17.8 MB
09 The Three classification models/002 Why can't we use Linear Regression_.mp4 17.8 MB
39 Time Series - Implementation in Python/003 Auto Regression Model - Basics.mp4 17.7 MB
28 CNN - Basics/002 Stride.mp4 17.4 MB
07 Linear Regression/016 Regression models other than OLS.mp4 17.3 MB
14 Simple Decision Trees/014 Evaluating model performance in Python.mp4 17.2 MB
02 Setting up Python and Jupyter Notebook/001 Installing Python and Anaconda.mp4 17.1 MB
10 Logistic Regression/007 Training multiple predictor Logistic model in R.mp4 16.5 MB
22 Creating Support Vector Machine Model in Python/004 X-y Split.mp4 15.9 MB
14 Simple Decision Trees/009 Dependent- Independent Data split in Python.mp4 15.9 MB
26 ANN in Python/001 Keras and Tensorflow.mp4 15.6 MB
37 Time Series - Preprocessing in Python/008 Time Series - Power Transformation.mp4 15.6 MB
07 Linear Regression/022 Heteroscedasticity.mp4 15.2 MB
14 Simple Decision Trees/003 The stopping criteria for controlling tree growth.mp4 14.6 MB
08 Classification Models_ Data Preparation/003 Importing the dataset into R.mp4 14.1 MB
06 Data Preprocessing/005 Importing the dataset into R.mp4 13.7 MB
02 Setting up Python and Jupyter Notebook/005 Arithmetic operators in Python_ Python Basics.mp4 13.4 MB
36 Time Series Analysis and Forecasting/001 Introduction.mp4 12.9 MB
42 Bonus Section/001 The final milestone!.mp4 12.4 MB
11 Linear Discriminant Analysis (LDA)/002 LDA in Python.mp4 12.0 MB
38 Time Series - Important Concepts/001 White Noise.mp4 11.9 MB
04 Basics of Statistics/002 Types of Statistics.mp4 11.5 MB
26 ANN in Python/005 Different ways to create ANN using Keras.mp4 11.3 MB
20 Support Vector Classifier/002 Limitations of Support Vector Classifiers.mp4 11.3 MB
19 Maximum Margin Classifier/004 Limitations of Maximum Margin Classifier.mp4 11.1 MB
34 Transfer Learning _ Basics/003 VGG16NET.mp4 10.9 MB
36 Time Series Analysis and Forecasting/003 Forecasting model creation - Steps.mp4 10.6 MB
22 Creating Support Vector Machine Model in Python/010 Classification model - Standardizing the data.mp4 10.2 MB
07 Linear Regression/001 The Problem Statement.mp4 9.8 MB
10 Logistic Regression/011 Evaluating model performance in Python.mp4 9.4 MB
19 Maximum Margin Classifier/001 Content flow.mp4 9.1 MB
10 Logistic Regression/005 Logistic with multiple predictors.mp4 8.9 MB
37 Time Series - Preprocessing in Python/010 Exponential Smoothing.mp4 8.8 MB
30 Creating CNN model in R/001 CNN on MNIST Fashion Dataset - Model Architecture.mp4 7.7 MB
34 Transfer Learning _ Basics/002 LeNET.mp4 7.3 MB
15 Simple Classification Tree/006 Advantages and Disadvantages of Decision Trees.mp4 7.2 MB
41 Time Series - SARIMA model/003 Stationary time Series.mp4 5.9 MB
22 Creating Support Vector Machine Model in Python/001 Regression and Classification Models.mp4 4.2 MB
42 Bonus Section/002 Congratulations & About your certificate.html 2.6 kB
23 Creating Support Vector Machine Model in R/003 More about test-train split.html 1.5 kB
01 Introduction/002 Course Resources.html 1.3 kB
31 Project _ Creating CNN model from scratch in Python/002 Data for the project.html 1.1 kB
0. Websites you may like/[FCS Forum].url 133 Bytes
0. Websites you may like/[FreeCourseSite.com].url 127 Bytes
0. Websites you may like/[CourseClub.ME].url 122 Bytes
0. Websites you may like/[GigaCourse.Com].url 49 Bytes

==查看完整文档列表==

上一个：[ CourseLala.com ] Udemy - Become a Great Baker #3 - Opera Cake Quartet2.6 GB
下一个：【全网寻花约良家】，第二炮，猎物中颜值最高，28岁舞蹈老师，情趣圆床房，香艳劲爆佳作 233.6 MB

种子标签

种子评价

优质的种子 (0) 假种子 (0) 有密码 (0) 低质量 (0) 有病毒 (0) 无法下载 (0)
欢迎对种子质量进行评价。

人气女优

北川ゆい Akira COCOLO Saiko あいだももあさのくるみあまいれもんいしかわ愛里いとうしいなうさみ恭香うちだまひろかぐやひめかとりこのみかないかほくすのき琴美クミコグレースくらもとまい（葉月ありさ）さとみ中村あみしいな純菜しのざきさとみ（三沢亜也）牧本千幸（つかもと友希）眞木ありさデヴィテラパトリックドミニカともさかまいともさか愛なごみもえひなこ

分享BT种子/磁力链接

亲，你知道吗？下载的人越多速度越快，赶快把本页面分享给好友一起下载吧^_^

2048BT

BT种子名称

[FreeCourseSite.com] Udemy - Machine Learning & Deep Learning in Python & R

分享给好友

BT种子基本信息

下载磁力链接

下载BT种子

文档列表

猜你喜欢

种子标签

种子评价

最近搜索

人气女优

最新番号

分享BT种子/磁力链接

友情链接