bmanobel Goto Github PK
Name: bmanobel
Type: User
Location: Spain
Name: bmanobel
Type: User
Location: Spain
Código Python y archivos csv con ejemplos para los ejercicios del Blog aprendemachinelearning.com
Code Repository for Machine Learning with PyTorch and Scikit-Learn
Machine Learning for Imbalanced Data, published by Packt
A complete ML study path, focused on TensorFlow and Scikit-Learn
Practice and tutorial-style notebooks covering wide variety of machine learning techniques
A collection of machine learning examples and tutorials.
Materials of the PyData Madrid monthly meetups
MeetUp Python_Sevilla group - "Intro to geographic data processing with Python"
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
This repository contains some Jupyter notebooks I've put together while working on machine learning topics.
Machine Learning Resources, Practice and Research
Repo to supplement my tutorial on Monte Carlo Simulations and Importance Sampling
Scikit-Learn, NLTK, Spacy, Gensim, Textblob and more
The repository contains notebooks written in Python about NLP applications. The first folder created in this repository maintains the implementation of multi-label text classification on movies dataset. In the long term this repository will include hands-on applications and notebooks for various field of the NLP discipline.
YSDA course in Natural Language Processing
Contains notebooks related to various transformers based models for different nlp based tasks
Jupyter notebooks for the Natural Language Processing with Transformers book
Implementation for the different ML tasks on Kaggle platform with GPUs.
NYU Deep Learning Spring 2021
A complete tutorial on using own dataset to train a CNN from scratch in Keras (TF & Theano Backend)-
Unsupervised Clustering of Time Series using Peer Group Analysis PGA
BEST SCORE ON KAGGLE SO FAR , EVEN BETTER THAN THE KAGGLE TEAM MEMBER WHO DID BEST SO FAR. The project is about diagnosing pneumonia from XRay images of lungs of a person using self laid convolutional neural network and tranfer learning via inceptionV3. The images were of size greater than 1000 pixels per dimension and the total dataset was tagged large and had a space of 1GB+ . My work includes self laid neural network which was repeatedly tuned for one of the best hyperparameters and used variety of utility function of keras like callbacks for learning rate and checkpointing. Could have augmented the image data for even better modelling but was short of RAM on kaggle kernel. Other metrics like precision , recall and f1 score using confusion matrix were taken off special care. The other part included a brief introduction of transfer learning via InceptionV3 and was tuned entirely rather than partially after loading the inceptionv3 weights for the maximum achieved accuracy on kaggle till date. This achieved even a higher precision than before.
Spanish Translation
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano
A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)
PyConES 2016 - py-reglas de asociacion talk
Statistics and Machine Learning in Python
Curso de Introducción a Machine Learning con Python
Python Programming @ WebValley 2019
Minicourse in Deep Learning with PyTorch
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.