My name is Eduardo Muñoz Sala, a Computer Science Engineer with more than 20 years coding, analyzing software requierements and deploying bussiness aplication. Linkedin profile.
This is my personal blog where I will be posting about machine learning and data science. Last two years I have been involved in a fascinating learning path, building some projects on ML that I am uploading to my github account. And the posts in this blog will describe some of them, explaining details or other relevant topics.
In this Trello board there is a complete list of certificates, specializations and courses I have complete last two years. And there are links to some of my projects and blog posts on Medium.
This board is changing and evolving.
- Machine Learning Engineer Nanodegree - Udacity
- Deep Learning Specialization - deeplearning.ai
- Microsoft Professional Program in Artificial Intelligence - Microsoft
- Microsoft Professional Program in Data Science - Microsoft
- Applied Machine Learning in Python Specialization - Coursera, Michigan University
In my github acount you can find some of my projects, developed during the last two or three years. There are some of them that I am still reviewing and cleaning, I will upload them in the next months including some posts to describe them.
This repository contains all the documents and code developed for the capstone project in the Machine Learning Engineer Nanodegree program. The project is about text summarization applying machine learning techniques like an extractive model based on sentence clustering and an abstractive model, a sequence to sequence model with attention and Pointer Generator.
An image classifier to predict if a cell is infected or not with malaria. This repo contain some simple convolutional networks, apply data augmentation and transfer learning. We also include notebooks and scripts to train in Azure ML Services
A classification problem on tabular data using decision trees and ensemble models like AdaBoost or XGBoost. Include an extensive Feature engineering and selection tasks.
A Keras Tensorflow model trained on Azure Machine Learning Services to identify accents in spectrograms of speech. An image classification problem solved using CNN, pre-trained models and data augmentation.
This repository contains many of the notebooks developed to analyze a dataset of mortgage approvals. This exercise is the capstone project in the Microsoft Professional Program in Data Science and the report included is the result of this analysis. Then as part of the capstone I developed a machine learning model to classify when a mortgage application would be accepted or not by the loan company. The ml model was developed using the Microsoft tool, Azure Machine Learning Studio.
a blogging platform that natively supports Jupyter notebooks in addition to other formats. ↩