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Model Checkpoint in Tensorflow | Save Best Model using Checkpoint and Callbacks
3.9K views • 2 years ago
12:29
Save Model in JSON file | Save model in YAML file | Save weights and model in h5 file HDF5
4.5K views • 2 years ago
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Confusion Matrix With Example | Precision, Recall, F1 Score and Support | Evaluate Model
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Named Entity Recognition (NER) model using Deep Neural Network | TimeDistributed Layer
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Multiple Output Model In Tensorflow2.0 | The Functional API
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Introduction To The Functional API | Build A Model With The Functional API In Tensorflow2.0
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Time Series Analysis Using Deep Neural Network | Stock Price Prediction System with LSTM
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Introduction to Conv1D | Sentiment Analysis using Convolutional Neural Network (CNN)
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Introduction To Long Short Term Memory (LSTM) | IMDB Sentiment Analysis Using LSTM In Tensorflow 2.0
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Introduction to Gated Recurrent Units | Sentiment Analysis using GRU Layer from Tensorflow2.0
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IMDB Sentiment Analysis Using SimpleRNN Layer From Tensorflow | Working With Sequential Data (Text)
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Sentiment Analysis | Learning Embedding For Words Of Corpus Using Embedding Layer | RNN In Tensoflow
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Sentiment Analysis Using Deep Neural Network (SimpleRNN) With Word2Vec Pretrained Word Embeddings
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Creating Environments In Anaconda On Local Machine
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Installing Keras And Other Libraries In Anaconda In Specific Environment On Local Machine
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Drawbacks Of One-hot Encoding | Introduction To Word Embeddings | Load And Use Pretrained Word2Vec
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VGG16 Pretrained Model For Cat Dog Classification Using Feature Extraction And Fine Tunning Method
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Pretrained Models | When And Why To Use Pre-trained Model | How To Use Pre-trained Model (Theory)
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Feature Maps Visualization Of CNN | Interpretation Of Output Of Conv2D And Maxpooling Layer
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Image Augmentation With Keras For Increasing Size Of Dataset | ImageDataGenerator TF Keras
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Introduction To Convolutional Neural Network | Convolutional Neural Network Example | Deep Learning
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People Card | Digital Visiting Card | Virtual Card | Get Search Enabled On Google By Your Own Name
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Accessing Google Drive In Colab | Working With Large File | Reading From File From Google Drive
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Training NN On CSV File Dataset In Google Colab Using Pandas Library To Extract And Process Dataset
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Model Summary | Plotting Model | Getting Layers With Weights | Saving Models | Loading Weight
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Need of Learning Rate Decay | Using Learning Rate Decay In Tensorflow 2 with Callback and Scheduler
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Learning Rate | Effect of High and Very Small Learning Rate | Using Learning Rate in Tensorflow 2.0
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