Setting Up Your Deep Neural Network Optimization Problem (Week 1 Summary)

Starting with normalizing our input features, why do we really need normalizing the input features on the first place? The simple answer is we normalize the input features so that the cost function is elongated so when the gradient descent is run, it makes it easier and faster to find its way to the minimum.

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Regularizing your Neural Network (Week 1 Summary)

This is part 2 summary of Prof Andrews specialization course "Improving Deep Neural Networks Hyperparameter, tuning, regularization, optimization" (Week1)

Regularization should be used when our neural network overfits the data. (And how'd we know if our NN overfits on data please refer Setting up Machine Learning Application) 

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Setting up your Machine Learning Application (Week 1 Summary)

This blog serves to provide summary for Prof Andrew ng deeplearning.ai specialisation course  "Improving Deep Neural Networks Hyperparameter tuning, Regularization & Optimization" 

A good high performance neural network largely depends on our choices how we set up our:

• training set
• development or dev set (validation set)
• test sets

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Exploring Istanbul with dad!

16 February 2018, what a lovely day it was! A daughter set on the journey to meet her dad whom she didn’t see for 3 long months. I settled here in Istanbul for doing master’s in Data Sciences. With the end of my semester, my dad planned a 3 days trip to see me at Istanbul. He then had to fly to California to meet my older sister who was waiting to see him with same impatience.

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Natural Language Inference - A large Annonated Corpus

Hello people! Here I will be giving you an overview to a research paper related to Natural Language Inference. This is one of my favorite topics of study for why I chose this particular amazing research paper. Natural language along being interesting is one of the hot topics of study today and there is lots and lots of research happening in this domain.

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