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+# Deeplearning
+
+I will update this repository to learn Deeplearning with Tensorflow and Keras
+
+
+[Day - 1](https://github.com/nursnaaz/Deeplearning/tree/master/01%20-%20Day%20-%201%20Neural%20Network%20Basics): 25-8-2019
+We Learnt about 
+
+1. Basic building blocks of Neural Network<br>
+2. Perceptron<br>
+3. Neurons<br>
+4. Hidden Layers<br>
+5. Linear regression with Neural Networks<br>
+6. Logistic regression with Neural Networks<br>
+6. No Linear Activation Function<br>
+7. tanh, step, logit, relu, elu<br>
+8. Back propagation<br>
+9. Vanishing and Exploding gradient descent<br>
+10. Ways to avoid Vanishing and Exploding gradient descent<br>
+11. How to mitigate over fitting ?<br>
+12. Tensorflow - Keras practical<br>
+
+
+[Day - 2](https://github.com/nursnaaz/Deeplearning/tree/master/02%20-%20Day%20-%202%20Convolution%20NN): 31-8-2019 
+1. Parameter explotion in image recognition
+2. Convolution layer - kernel , filter, Stride, Padding, feature map
+3. Pooling Layer - max, min, average
+4. CNN architecture
+5. Keras implementation
+6. Image recognition in comparison with Basis NN and CNN
+7. Advanced Deep CNN
+8. Pre Trained Models
+9. Transfer Learning - Resnet50
+10. Image Agumentation
+11. Tensor board
+12. Opencv, Yolo3
+13. Sample Hackathon