LightSpeedAC

What is Deep Learning Specialization? The Deep Learning Specialization is the group of courses by Andrew Ng and his staff over at deeplearning.ai, which is a comprehensive course that starts at the extreme basics of Neural Networks (a part of Machine Learning) and ends up teaching you concepts applicable in various cutting-edge fields of AI. If you haven't yet learnt from Andrew Ng, all I can say is you're in for a ride! His teaching is excellent and the learner's understanding is ensured. I have done all four courses, with 100% grade and certification, and will review them below. But before that... Proof 1.   Neural Networks and Deep Learning This course is intended to teach you what is Deep Learning  and what it means to the technology world. Although the course starts with Logistic Regression, the course eventually ends up training first shallow Neural Networks and then deep NNs. If you have never done an AI course, no worries this course got you covered....

  What is the TensorFlow: Data & Deployment Specialization? The TensorFlow: Data and Deployment specialization is deeplearning.ai' s new group of courses and is intended to teach you how to practically use your DL skills to make practical applications. It is co-taught by Andrew Ng and Laurence Moroney, both seasoned veterans in AI and DL. I will give a detailed review of the first course below. I am trying to keep the content coming while doing the course myself! 1. Browser-Based models with TensorFlow.jS This course is intended to teach you how to set up a browser-based model using TensorFlow's browser equivalent- TfjS.  It shows the necessary JavaScript required for training models. It must be noted that tfjs is not direct TensorFlow! It's a different version, and they have few differences, which are correctly taught in the course. If you are used to Andrew Ng lectures, this isn't like that. The course assumes that you know Deep Learning, so most talks...

LightSpeed intro to ConvNets ________________________________________________ Unless you're experienced or have read the LightSpeed intro to DL, please see here before reading this. --------------------------------------------------------------------------------- In this post, you'll learn about- What are Convolutions? Why Convolutions work great (optional) Keras and TensorFlow (compulsory) How to make a Neural Network that can classify pictures depending on objects! What are ConvNets? Now, what are  ConvNets ? They are Neural Networks having Convolutions. Okay, so what are Convolution s ?  Convolutions, informally, are mathematical functions. Now, to convolve the above matrices, we take the second smaller matrix, then we imprint it on the first possible 2 by 2 chunk of the other as shown below. So, this will be the first value in the output matrix- = (4*1) + (2*0) + (0*0) + (3*1) = 7 Similarly, you may be able to calculate that the next ...

LightSpeed intro to DL In this post, you'll learn about- Basic necessities of DL theory Keras and TensorFlow (optional) How to make a Neural Network that can identify digits in a picture! Basic Necessities of Deep Learning Theory Now, what is Deep Learning ? It is, plainly the art of training Neural Networks . Okay, so what are Neural Networks? They are just another type of Machine Learning model, which apparently work like the brain. And now, two questions remain- 'What do they do?' and 'How do they work?' The answer to the first question is that they first predict some output for a problem using layers , with randomly initialized parameters. Then, after seeing how far they are from the actual truth, they change their settings to obtain lesser loss or distance from the truth.  Now for the second question, the answer is much less mystified and more mathematical. It computes a non-linear function (usually a ReLU of the (input if it's the fir...