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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 Name About Status
1. Intro to Tensorflow DL This covers Tensorflow Basics like Placeholders, Variables, Constants etc. It also coveres "Tensorflow Estimator API" for Regression & Classification with projects. Completed
2. Convolutional Neural Networks This covers the basics of CNN along with some basic projects. Completed
3. Recurrent Neural Networks This covers the basics of RNN along with time series prediciton project. Completed
4. Tensorflow Abstractions & Tensorboard This covers various TF Abstractions like Keras, estimator etc. with Tensorboard. Completed

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Deep Learning Projects using Tensorflow.

Topics

deep-learning tensorflow neural-networks tensorflow-tutorials python35

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