In this article, I am going to introduce how I develop an ML-based web application that can predict the odds of individual players and sides to secure a rebound on the court.

First of all, let me show what the app eventually looks like:

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Go check out http://okc-thunder-rebounds.herokuapp.com/ (image by author)

As is indicated from the image above, users will be able to get the probability for each player/side to get the rebound, which is useful to basketball operators when they need to arrange tactics about rebounding. And some of the takeaways from the GIF above are:


Data Visualization

Using Easier Syntax than Plotly’s

If you follow the trending data science projects frequently enough, it’s not difficult for you to find that Plotly, which is born for interactive data visualization, is so dominative. I admit that Plotly is useful to plenty of degrees, except when you are not experienced with it and need to produce something immediately.

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Photo by William Iven on Unsplash

In this article, I am going to introduce a method that is seldom used but easily mastered: creating interactive plots using the well-known matplotlib! This requires nothing but your knowledge of matplotlib.

What do we need?

To assist with matplotlib, all we need is to import the package ipywidgets. Ipywidgets is a built-in library that provides controls to express codes in an interactive manner. Thus users can manage their visualizations or plots by controlling the widgets so that your notebook will be a lite application lookalike. …


Trade war, COVID-19, and all other stuff that I met expectedly or unexpectedly during my journey as a foreign student

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Photo by frank mckenna on Unsplash

The moment when I clicked to submit my answer to the “final” final exam, my life at Boston University unofficially came to the end (because our diploma certifies officially that I complete this program one month later :0). So did my career as a student. Generally speaking, this is a bittersweet experience for me as a foreign student in the United States where so many issues went out of my control while I gained a plethora of pleasure as well. …


With Flask,sklearn and MongoDB

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Image by mohamed Hassan from Pixabay

This summer I was so honored to have a chance and work with Massachusetts Immigrant & Refugee Advocacy Coalition (MIRA) to continue their census survey and services which were dramatically affected by the COVID-19 pandemic. I led a team that is responsible to build chatbots on some popular social media platforms, including Facebook and WhatsApp, among the immigrant communities. And this article is a quick rundown of the process that I went through and the solutions to some questions that I met during the development.


Leveraged Natural Language Processing (NLP) and Computer Vision (CV)

This summer I was privileged to collaborate with Made With ML to experience a meaningful incubation towards data science. I chose the awesome MovieLens dataset and managed to create a movie recommendation system that somehow simulates some of the most successful recommendation engine products, such as TikTok, YouTube, and Netflix.

This article is going to explain how I worked throughout the entire life cycle of this project, and provide my solutions to some technical issues.

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Image by Gerd Altmann from Pixabay

Ideas

At first glance at the dataset, there are three tables in total:


Predicting 2019/20 champion of UEFA Champion League after suspension using Machine Learning

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Photo by Alex Motoc on Unsplash

The past few months must be not easy for millions of soccer fans including me. As a die-hard fan of Real Madrid, I have already watched the highlights of Ronaldo, Raúl over and over again, trying to fulfill the excitement brought my favorite side but taken by COVID-19. But the good news is, soccer is back: three weeks ago, UEFA announced that from quarter-finals, UEFA Champion League (UCL) will be back in early August, and all fixtures will be single-elimination and released all the fixture draws. …


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(Image by author)

I once insisted that only the Kaggle competition winners are able to show off their background, now I just found an alternative for every rookie of Kaggle to showcase their endeavors without a decent rank of leaderboard!

What can we use our work in a Kaggle competition for? Obtaining a decent rank, and possibly getting a lot of rewards, this answer may sound good to some geniuses. But what about you are not intelligent enough? Would this competition totally meaningless? Definitely no! Kaggle as the biggest community for data scientists and machine learning enthusiasts, is not only for ranks and money, but also a perfect platform to enhance our data scientific/modeling techniques.

In the rest of the article, I will introduce a way to show what you have done in a Kaggle competition, which is a very useful portfolio especially when you fail to rank on the top of the leaderboard, and more importantly to impress your interviewers! …

About

Memphis Meng

Grad student @ Boston University, aspiring data scientist and sports analyst. Buy me a coffee now(https://www.buymeacoffee.com/MemphisMeng)!

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