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DataSets
DataSets
Reinforcement_Learning
Reinforcement_Learning
Tensorflow basics
Tensorflow basics
Recurrent Neural Networks.ipynb
Recurrent Neural Networks.ipynb
01-Linear-Autoencoder-for-PCA-Exercise.ipynb
01-Linear-Autoencoder-for-PCA-Exercise.ipynb
02-Time-Series-Exercise.ipynb
02-Time-Series-Exercise.ipynb
06-Regression-Exercise.ipynb
06-Regression-Exercise.ipynb
08-Classification-Exercise.ipynb
08-Classification-Exercise.ipynb
Activation Function.ipynb
Activation Function.ipynb
CIFAR-10 using Keras.ipynb
CIFAR-10 using Keras.ipynb
Convolutional_Neural_Networks.ipynb
Convolutional_Neural_Networks.ipynb
Currency_Classification.ipynb
Currency_Classification.ipynb
Deep_Learning.ipynb
Deep_Learning.ipynb
Dimensionality_Reduction_With_Linear_Autoencoder.ipynb
Dimensionality_Reduction_With_Linear_Autoencoder.ipynb
Fashion_MNIST.ipynb
Fashion_MNIST.ipynb
Forward_Propagation.ipynb
Forward_Propagation.ipynb
INITIALIZERS.ipynb
INITIALIZERS.ipynb
INNER_LAYER_REPRESENTATION.ipynb
INNER_LAYER_REPRESENTATION.ipynb
Improving_Performance.ipynb
Improving_Performance.ipynb
Iris_Dataset_Deep_Learning_Project.ipynb
Iris_Dataset_Deep_Learning_Project.ipynb
MNIST_Dataset_Project.ipynb
MNIST_Dataset_Project.ipynb
Manual Neural Network.ipynb
Manual Neural Network.ipynb
Manual_Neural_Network.ipynb
Manual_Neural_Network.ipynb
Manual_RNN_Using_TF.ipynb
Manual_RNN_Using_TF.ipynb
Movie_Review_Sentiment_Analysis.ipynb
Movie_Review_Sentiment_Analysis.ipynb
Neural_Network_1.ipynb
Neural_Network_1.ipynb
OOPs_Concepts.py
OOPs_Concepts.py
OPTIMIZERS.ipynb
OPTIMIZERS.ipynb
README.md
README.md
RNN_with_TF.ipynb
RNN_with_TF.ipynb
Saving -and-Loading-Models.ipynb
Saving -and-Loading-Models.ipynb
Tensorflow_Basic_Syntax.ipynb
Tensorflow_Basic_Syntax.ipynb
Tensorflow_Classification_Example.ipynb
Tensorflow_Classification_Example.ipynb
Tensorflow_Graphs.ipynb
Tensorflow_Graphs.ipynb
Tensorflow_Regression_Example.ipynb
Tensorflow_Regression_Example.ipynb
Variables_&_Placeholders_in_Tensorflow.ipynb
Variables_&_Placeholders_in_Tensorflow.ipynb
Word2Vec_with_tensorflow.ipynb
Word2Vec_with_tensorflow.ipynb
cal_housing_clean.csv
cal_housing_clean.csv
pima-indians-diabetes.csv
pima-indians-diabetes.csv
tensorflow_speech_recognizer.py
tensorflow_speech_recognizer.py

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Deep Learning using Tensorflow

This repository contains the code for Tensorflow Tutorials for Deep Learning from Starting to End. All the code is written using Python3.

Requirements

1. Python 3.5+

2. Tensorflow (Latest Version)

3. IPython Jupyter Notebook

Code List

S.No.Folder NameAboutStatus
1.Intro to Tensorflow DLThis covers Tensorflow Basics like Placeholders, Variables, Constants etc. It also coveres "Tensorflow Estimator API" for Regression & Classification with projects.Completed
2.Convolutional Neural NetworksThis covers the basics of CNN along with some basic projects.Completed
3.Recurrent Neural NetworksThis covers the basics of RNN along with time series prediciton project.Completed
4.Tensorflow Abstractions & TensorboardThis covers various TF Abstractions like Keras, estimator etc. with Tensorboard.Completed

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Deep Learning Projects using Tensorflow.

Topics

deep-learningneural-networkspython35tensorflowtensorflow-tutorials

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