Welcome to my blog!
I'm a Senior Data Scientist at Goshaba, with a passion for tennis and a keen interest in applying data science to sports analytics.
This space is where I share my projects and learnings, aiming to make data science accessible and exciting.
Join me as we explore the fascinating intersection of data, sports, and learning.
Let's decode the world of data together!
1 class Person:
2 def __init__(self):
3 self.name = "Monpezat"
4 self.surname = "Baptiste"
5 self.passions = ["Data Science", "Tennis"]
6 self.age = 29
7 self.city = Bordeaux
8
Things I love
Data Science
I'm captivated by the power of data science to unlock hidden patterns and insights.
It's a tool that transforms raw data into meaningful information, fueling informed decisions and innovative solutions.
Sport Analytics
As a tennis enthusiast, I find the application of data science in sports thrilling.
It's a game-changer, enhancing performance, strategy, and understanding of the game.
Programming
The art of coding is like a creative puzzle to me.
It's the backbone of all digital solutions, enabling us to build, innovate, and explore the limitless world of technology.
About Me
My Skillsets
Dash
Plotly
SQL
TensorFlow
Pytorch
MongoDB
Django
Scikit-learn
Pandas
Side Projects
Tic Tac Toe with Minimax Algorithm
This project consisted in developing a Tic Tac Toe in React. I implemented the minimax algorithm with alpha/beta pruning. Minimax is a decision rule used in artificial intelligence, decision theory, game theory, statistics for minimizing the possible loss for a worst case (maximum loss) scenario. Can you beat this AI ? Let's give it a try !
Hand Sign Challenge using React and Tensorflow āš¼
Do you know the TikTok hand signs challenge ? The challenge tasks participants to copy a list of hand emojis that appear on your screen. This app uses a neural network to predict hand signs from your camera and checks that you correctly copy the list of emojis.
Twitter Hashtags top trends with Spark Streaming.
How to deal with live streaming data ? I built a streaming pipeline with spark that processes live tweets coming from the twitter api.The stream processing extracts hashtags from tweets and count them in a 10 minutes window. The count is then sent to the front-end to visualize Hashtags top trends.Doing this project, I learned a lot about spark, docker as well as nginx for web proxy.
Get In Touch
Thank You
Do You Have Any Queries?