What Went Wrong for the L.A Lakers

Lakers Winning the 2020 NBA Championship. Source: USA Today

Flashback to last October. The NBA was finishing up a successful season in the Disney World Bubble ,and the Los Angeles Lakers had just won their 17th championship. Lebron James was named Finals MVP and Anthony Davis won his first championship ring. The trade for Anthony Davis paid off great dividends. Life is good for the Lakers.

Then came the offseason. According to many analysts, the Lakers got much, much better by adding talent such as Dennis Schroder, Sixth Man of the Year Montrel Harrel, and former NBA champion Marc Gasol. While they…


Does Machine Learning Meet our Expectations?

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I remember back in high school where some of my friends were talking about machine learning. They were mentioning a lot phrases such as neural networks, overfitting, etc. At the time, I had no idea what machine learning was. However, over the past year, I dedicated myself to mastering the art of machine learning. Machine learning isn’t a science, it is an art. To enjoy its beauty, you have to continuously look to improve your knowledge about it. …


Using Basic Python to Implement a Simple Neural Network From Scratch

Photo by Florian Olivo on Unsplash

Welcome to Deep Learning with PyTorch Part #4! If you are new, feel free to take a look at the previous parts. The previous parts are all on my Medium page. As a refresher, in the last article, I walked through the mathematics of feed-forward. Feed-Forward is one of the fundamental concepts of neural networks. Feed-forward is a process in which your neural network takes in your inputs, “feeds” them through your hidden layers, and “spits” out an output.

In this article, I will provide a thorough implementation of feed-forward in Python. All code presented in this article can be…


Conquering the Foundations of Deep Learning

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It is one thing to know what an artificial neural network (ANN) is and it is another thing to know how it actually works. If you ever want to utilize deep learning to build cool projects, it is essential that you understand ANNs. The concepts from ANNs can be applied to nearly every other type of neural network. When it comes to ANNs, there are 2 major concepts to understand: Feed-Forward and Back-propagation. Both of these concepts require a lot of in-depth understanding, so I will split them up into different articles. In this article, we will get our hands…


How I Turned a Negative Time into an Opportunity to Learn.

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The Beginning

It was March 2020. I was a senior in high school and was ecstatic to go to Walt Disney World for my senior trip. I packed everything properly, and went to sleep at 9 PM so that I can catch my 3 AM flight. At the time, I had heard about the coronavirus, but I didn’t think much about it. Like many others, I thought it was just a virus that would go away, so I didn’t pay too much attention to it. Boy, was I wrong. At 1 AM, the superintendent sent out an email stating that the Disney…


If you have studied anything related to deep learning or machine learning, you have probably heard the phrase “neural networks”. What exactly are these neural networks? How do they work? What makes them so powerful? In this article, I shall break down neural networks. This article is the second part of my Deep Learning with PyTorch series. If you haven’t already checked out part #1, I would highly suggest it. In part #1, I discuss the high-level concept of deep learning. However, enough about part #1, let’s dive into part #2.

A simple Artificial Neural Network, Image Link: main-qimg-3e46e8f59e28a696c0127e42be477dfb

What are Neural Networks?

On an abstract level, neural networks are models that…


Beginning the journey of utilizing PyTorch to conquer Deep Learning

Photo by Matt Duncan on Unsplash

This will be the first part of my series: Deep Learning with PyTorch. As I am learning the ins and outs of deep learning & PyTorch, I thought it would be beneficial for me to share my learnings with the community. As a result, I have created this series. My hope is that by the end of this series, you will be proficient in PyTorch & be knowledgable enough to apply deep learning. Also, in this series, I highly recommend that you go beyond the information presented in the articles to gain a full in-depth understanding of deep learning. …

Jinal Shah

A.I practioner, Tech Geek, Sports Enthusiast.

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