👋 Hi there, it’s Lina …
I’m a freelance data scientist based in France 🇫🇷🥖 who loves diving into the nitty-gritty of data science projects.
Through my blog posts, I explore various data science topics, providing simple yet detailed explanations. I bring these concepts to life by applying them to real-world use cases, describing the results, and sharing the code on Github.
💬 If you’re interested in collaborating or have any data science project ideas you’d like to discuss, feel free to contact me on Linkedin. I’m always looking for exciting opportunities to put my skills to work.
👉 If you’re looking to level up your data science skills and stay on top of the latest trends, subscribe to my Medium page here for only $5/month (you’ll also get access to all the articles published on Medium).
Why Do I Write Articles?
Writing technical blog posts that include real-world use cases can be time-consuming. Plus, the rapid progress of AI can make the effort seem futile. So why write in this case?
I write technical blog posts for several reasons.
- Firstly, I’m an avid data science enthusiast. I always feel the need to go beyond passive reading and get my hands dirty by implementing new concepts and techniques.
- But it’s not just about learning for myself. Through my work as a consultant with many companies, I noticed a gap between research and practice. While many research papers showcase great models and approaches, there is often a lack of implementation and real-world examples. I aim to bridge this gap by taking these cutting-edge concepts and applying them to real-world use cases, then sharing my results and code on Github for others to use.
- Lastly, I enjoy sharing my knowledge with others. Through my blog posts, I hope to inspire others to explore data science further and empower them to implement these techniques in their own work.
Survival Analysis: Predict Time-To-Event With Machine Learning (Part I)
Practical Application to Customer Churn Prediction
Survival Analysis: Leveraging Deep Learning for Time-to-Event Forecasting
Practical Application to Rehospitalization
Graph Neural Networks: Merging Deep Learning With Graphs (Part I)
When It Comes to Node Classification
Graph Neural Networks: Link Prediction (Part II)
When It Comes to Forecasting Connections Within a Network
Graph Neural Networks: Graph Classification (Part III)
When It Comes to Labeling Whole Graphs, Not Just Nodes
Fraud Detection with Graph Analytics
Leveraging the Network Structure of the Use Case to Boost Predictive Performance
Deep Learning & Time Series
Deep Learning for Time Series Forecasting: Is It Worth It? (Part I)
Using RNNs & DeepAR Models to Find Out
Can Deep Learning Change the Game for Time Series Forecasting? (Part II)
We introduce the MQ Forecaster & Transformer models and compare their performances against classic ML methods.
Evolutionary Decision Trees: When Machine Learning draws its Inspiration from Biology
Discover Evolutionary Decision Trees
How can Machine Learning algorithms include better Causality?
In recent years, machine learning algorithms have known great success. Thanks to the availability of an important amount…
Understanding Happiness Dynamics with Data (Part 1)
A Descriptive Analysis at the Country Level
Understanding Happiness Dynamics with Machine Learning (Part 2)
In-depth Analysis of Happiness Drivers
Deep Q Network: Combining Deep & Reinforcement Learning
Uncover the Power of Deep Reinforcement Learning
AI-Driven Tax Policy: What It Would Look Like?
Discover what Reinforcement Learning can bring to Tax Policy Design