As part of the MLND program, I've run a set of projects aiming to learn machine learning by building and applying predictive models to massive data.
I have developed a skill set that allows me to develop machines and systems that automatically improve. I have built, evaluated, and optimized machine learning models including classification, regression, clustering, and recommendation using the most efficient Python libraries for machine learning such as pandas, NumPy, SciPy, and scikit-learn, but also the open-source library Tensorflow for deep learning.
The following projects goes from the prediction of housing prices using linear regression techniques, to the training of a smartcab to drive by itself using a reinforcement learning model.
| Section | Project | Status |
|---|---|---|
| Exploratory Project | Titanic Survival Exploration | ✔️ |
| Model Evalution and Validation | Predicting Boston Housing Prices | ✔️ |
| Supervised Learning | Finding Donors for CharityML | ✔️ |
| Unsupervised Learning | Creating Customer Segments | ✔️ |
| Reinforcement Learning | Train a Smartcab to Drive | ✔️ |
| Deep Learning | Image Classification | ✔️ |
| Machine Learning Specializations | Capstone Project | - |
Contact me anytime for anything about my projects or machine learning in general. I'd be happy to help you 😉
- Twitter: @gdangel0
- Linkedin: Grégory D'Angelo
- Email: [email protected]