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Basketball Analytics: Predicting Win Shares

Analysis Objective: Can we predict individual win shares of NBA players using other basketball metrics? The data used for this analysis is from the 2016–17 and 2017–2018 NBA Season, using Basketball-Reference. Essentially, I used data from the 2016–2017 NBA season to create our model and stats from the most recent

Backpropagation for people who are afraid of math

Backpropagation is one of the most important concepts in machine learning. There are many online resources that explain the intuition behind this algorithm (IMO the best of these is the backpropagation lecture in the Stanford cs231n video lectures. Another very good source, is this), but getting from the intuition to

How to Automatically Import Your Favorite Libraries into IPython or a Jupyter Notebook

No more typing “import pandas as pd” 10 times a day If you often use interactive IPython sessions or Jupyter Notebooks and you’re getting tired of importing the same libraries over and over, try this: Navigate to ~/.ipython/profile_default Create a folder called startup if it’s not already there Add a new

Kaggle Days 2019 in Paris

Kaggle Days are the first global offline events series for Data Scientists and Kagglers. Such a great event provides an opportunity to both create and build the data science community. First-ever event called Kaggle Days in Warsaw succeeded in 2018. Over 100 participants learned from Kaggle Grandmasters in lively presentations

Boosting and AdaBoost clearly explained

II. Introduction to Boosting a. Concept The intuition described above can be described as such : Train the model h1 on the whole set Train the model h2 with exaggerated data on the regions in which h1 performs poorly Train the model h3 with exaggerated data on the regions in which h1

Neural Quantum States

One of the most challenging problems in modern theoretical physics is the so-called many-body problem. Typical many-body systems are composed of a large number of strongly interacting particles. Few such systems are amenable to exact mathematical treatment and numerical techniques are needed to make progress. However, since the resources required

How Artificial Intelligence (AI) is Adding New Horizons to Cybersecurity Solutions?

AI For Cybersecurity McCarthy and Minsky described Artificial Intelligence as a task performed by a machine, which if, performed by a human instead will require a great deal of intelligence. A collective data of all the behavioral qualities are required to make the precise decision. These behavioral qualities are planning,

How to Find Your Partner and Grow Your Relationship

Valentine’s Day is arriving. Whether or not you will share this day with someone, you probably thought about how your ideal partner and relationship should look like. If you want to know what data (source in footnote) says about “how to find your partner and grow your relationship?”, we can

The Future and Philosophy of Machine Consciousness

Can a machine think Short answer: Sure, why not. Long answer: It’s complicated. In 1950, Alan Turing, known as the father of modern computing and artificial intelligence, wondered the same thing. In an attempt to answer, he coined the famous Turing test. Put simply: “The Turing test, developed by Alan Turing

NLP and Sarcasm: What’s the Deal?

Sarcasm is incredibly hard for chatbots and NLP applications. Here, we’ll take a look at why. Sarcasm or Not? As humans, you and I can look at these two chats and determine that in the first the person appears to be sincere while in the other comes off sarcastic and cold simply

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