Improving-Deep-Neural-Networks

This Repository contains the Programming assignments completed under second course of Deep Learning specialisation(Coursera)

Skills learnt

• Best practices to train and develop test sets
• Analyzing bias/variance for building deep learning applications
• Using standard Neural Network techniques such as initialization, L2 and dropout regularization, hyperparameter tuning, batch normalization, and gradient checking
• Implementation and application of variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam
• Checking for optimization algorithm's convergence and implementation a Neural Network in TensorFlow

Result

• Certificate :- https://coursera.org/share/e08dc916b2b879cad32ea4bfab7afc12