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دسته بندی دوره ها

Complete Deep Learning In R With Keras & Others

سرفصل های دوره

Deep Learning: Master Powerful Deep Learning Tools in R Like Keras, Mxnet, H2O and Others


1 - INTRODUCTION TO THE COURSE The Key Concepts and Software Tools
  • 1 - Introduction to the Course
  • 2 - Data and Code.html
  • 3 - Install R and RStudio
  • 4 - Install MXnet in R and RStudio
  • 5 - Install Mxnet in R Written Instructions.html
  • 6 - Install H2o
  • 7 - What is Keras
  • 8 - Install Keras in R.html
  • 9 - What Are the Most Common Data Types We Will Encounter

  • 2 - Basic Data Access & PreProcessing in R
  • 10 - Read in Data From CSV and Excel Files
  • 10 - Resp1.csv
  • 10 - boston1.xls
  • 10 - l5-csv-excel.zip
  • 10 - winequality-red.csv
  • 11 - Read in Data from Online HTML TablesPart 1
  • 11 - readhtml-xml.zip
  • 12 - Read in Data from Online HTML TablesPart 2
  • 12 - readhtml-rcurl.zip
  • 13 - Working with External Data in H2o
  • 14 - Remove NAs
  • 14 - l6-removena.zip
  • 15 - More Data Cleaning
  • 15 - l7-more-data-clean.zip
  • 16 - Introduction to dplyr for Data SummarizingPart 1
  • 16 - dplyr-part1.zip
  • 17 - Introduction to dplyr for Data SummarizingPart 2
  • 17 - dplyr-part2.zip
  • 18 - Exploratory Data AnalysisEDA Basic Visualizations with R
  • 18 - l8-eda.zip

  • 3 - Some Theoretical Foundations
  • 19 - Difference Between Supervised & Unsupervised Learning
  • 20 - Theory Behind ANN Artificial Neural Network and DNN Deep Neural Networks
  • 21 - What Are Activation Functions

  • 4 - Build Artificial Neural Networks ANN in R
  • 22 - Neural Network for Binary Classifications
  • 22 - UCI-Credit-Card.csv
  • 22 - neural-binary-class.zip
  • 23 - Evaluate Accuracy
  • 24 - Implement a MultiLayer Perceptron MLP For Supervised Classification
  • 24 - glassClass.csv
  • 24 - mlp.zip
  • 25 - Neural Network for Multiclass Classifications
  • 25 - neural-multiclass.zip
  • 26 - Neural Network for Image Type Data
  • 26 - image-class.zip
  • 27 - Multiclass Classification Using Neural Networks with caret
  • 27 - fashion-class.zip
  • 28 - Implement an ANN with H2o For MultiClass Supervised Classification
  • 28 - h2o-ann.zip
  • 29 - Implement an ANN Based Classification Using MXNet
  • 29 - class-mxnet.zip
  • 30 - Implement MLP With Keras
  • 30 - mlp-mnist-keras.zip
  • 31 - Keras MLP On Real Data
  • 31 - iris-mlpk.zip
  • 32 - Keras MLP For Regression
  • 32 - iris-regression.zip
  • 33 - Neural Network for Regression
  • 33 - neural-regression.zip
  • 34 - More on Artificial Neural NetworksANN with neuralnet
  • 34 - neural-regression2.zip
  • 35 - Implement an ANN Based Regression Using MXNet
  • 35 - regression-mxnet.zip
  • 36 - Identify Variable Importance in Neural Networks
  • 36 - neuralnet-variableimp.zip

  • 5 - Build Deep Neural Networks DNN in R
  • 37 - Implement a Simple DNN With neuralnet for Binary Classifications
  • 37 - simple-dnn-neuralnet.zip
  • 38 - Implement a Simple DNN With deepnet for Regression
  • 38 - deepnetr.zip
  • 39 - Implement a DNN with H2o For MultiClass Supervised Classification
  • 39 - h2o-dnn-3hidden.zip
  • 40 - Implement a Less Intensive DNN with H2o For Supervised Classification
  • 40 - h2o-dnn-2hidden.zip
  • 41 - Implement a DNN With Keras
  • 42 - Identify Variable Importance
  • 42 - h2o-varimp.zip
  • 43 - Implement MXNET via caret
  • 43 - mxnet-caret.zip
  • 44 - Implement a DNN with H2o For Regression
  • 44 - h2o-regression.zip
  • 45 - Implement a DNN with Keras For Regression
  • 45 - keras-dnn-bh.zip
  • 46 - Implement DNN Regression With Keras Real Data
  • 46 - keras-dnn-ames.zip

  • 6 - Unsupervised Classification with Deep Learning
  • 47 - Theory Behind Unsupervised Classification
  • 48 - Autoencoders for Unsupervised Learning
  • 49 - Autoencoders for Credit Card Fraud Detection
  • 49 - creditcard.csv
  • 49 - h2o-autoencoders.zip
  • 50 - Use the Autoencoder Model for Anomaly Detection
  • 50 - implement-auto.zip
  • 51 - Autoencoders for Unsupervised Classification
  • 51 - cancer-tumor.csv
  • 51 - h2o-ann-unsup.zip
  • 52 - Autoencoders With Keras
  • 52 - keras-auto-digits.zip
  • 53 - Keras Autoencoders on Real Data
  • 54 - Stacked Autoencoder With Keras
  • 54 - creditcard.csv
  • 54 - stacked-auto.zip
  • 55 - Keras For Outlier Detection
  • 56 - Find the Outlier
  • 57 - Outlier Detection For Cancer With Keras
  • 57 - cancer-tumor.csv
  • 57 - outlier-tumor.zip

  • 7 - Convolutional Neural Networks CNN
  • 58 - What is a CNN
  • 59 - Implement a CNN for MultiClass Supervised Classification
  • 60 - More About Our CNN Model Accuracy
  • 61 - Set Up CNN With Keras
  • 62 - More About CNN With Keras
  • 63 - Implement Keras CNN On Real Images
  • 64 - Some More Explanations
  • 65 - Improve CNN Performance
  • 65 - cnn-lung-improve.zip
  • 66 - CNN For Multiclass Classification
  • 66 - fruit.zip

  • 8 - Working With Textual Data
  • 67 - Basic PreProcessing of Text Data
  • 67 - enron-emails.csv
  • 67 - text-pre.zip
  • 68 - Detect Frauds Using Keras Autoencoders on Text Data
  • 68 - enron-emails.csv
  • 68 - text-auto.zip
  • 69 - Word Embeddings For Classifying Fraud
  • 69 - enron-emails.csv
  • 69 - word-embed.zip
  • 70 - Word Embeddings For Classifying FraudGloVe
  • 70 - enron-emails.csv
  • 70 - word-embed-glove.zip

  • 9 - Recurrent Neural Networks RNN
  • 71 - Some theoretical foundations
  • 72 - Use RNNs for Text Classification
  • 72 - enron-emails.csv
  • 73 - Use RNNs for Temporal Data
  • 73 - rnn-temporal.zip
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    مدت زمان: 475 دقیقه
    تاریخ انتشار: 22 دی 1401
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