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Predict Basketball Champions using Neural Networks, Keras and Classification Model

In this project, we are going to predict which team will win the NCAA basketball tournament of coming 2017 based on past historical data.
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What will you learn

  • Introduction to Neural Networks
  • Hands-on Neural Network
  • Introduction to Keras
  • Prediction using Classification model
  • Preprocessing of Data

What will you get

  • Access to recording of the complete project
  • Access to all material related to project like data files, solution files etc.

Prerequisites

  • Anaconda 2.7 version
  • keras, seaborn package
  • Understanding about how keras package and neural networks works

Project Description

Another year, another chance to predict the upsets, call the probabilities and put your bracketology skills to the leaderboard test. In this hackerday, we will once again attempt to predict the outcomes of this year's US men's college basketball tournament. But unlike most hackerday, we will pick the winners and losers using a combination of rich historical data and computing power, while the ground truth unfolds on national television.

Data Introduction:

If you are unfamiliar with the format and intricacies of the NCAA tournament, we encourage reading the wikipedia page before diving into the data. The data description and schema may seem daunting at first but is not as complicated as it appears.

As a reminder, you are encouraged to incorporate your own sources of data. We have provided team-level historical data to jump-start the modeling process, but there is also player-level and game-level data that may be useful.

We extend our gratitude to Kenneth Massey for providing much of the historical data.

What to predict:

  1. We will predict the probabilities for every possible matchup in the past 4 NCAA tournaments (2013-2016).
  2. We will predict the probabilities for every possible matchup before the 2017 tournament begins.

Instructors

 
Shaik

Data Scientist / Business Consultant at GE

3 years of rich working experience in BIG Data, Business Intelligence & Analytics with CMMI Level 5 Organizations in BFSI, Manufacturing Sector. Excellent written and oral communications, strong analytical and problem solving capabilities. Constantly learning and experimenting emerging open source tools and technologie see more...