Pinned Repositories
2016-ml-contest
Machine learning contest - October 2016 TLE
AI_ML_Seismic_Log
This is for AI prediction using seismic attributes
ATPESC_MachineLearning
avenir
Set of Machine Learning and Stochastic Optimazion tools based on Hadoop, Spark and Storm https://pkghosh.wordpress.com/
awesome-open-geoscience
Curated from repositories that make our lives as geoscientists, hackers and data wranglers easier or just more awesome
bayesian-neural-network-mnist
Bayesian neural network using Pyro and PyTorch on MNIST dataset
BERT_medical_QA
Question Answering on emrQA dataset (clinical notes) using BERT
ltr-demo
A simple LTR Demo
gopakumargeetha's Repositories
gopakumargeetha/Deep-Reinforcement-Learning-Algorithms-with-PyTorch
PyTorch implementations of deep reinforcement learning algorithms and environments
gopakumargeetha/blog_stuff
experiments and snippets used on the blog
gopakumargeetha/tutorials-2016
Geophysical Tutorials for 2016
gopakumargeetha/PyTorch-Geometric-YooChoose
This is a tutorial for PyTorch Geometric on the YooChoose dataset
gopakumargeetha/segyio-notebooks
Notebooks with examples and demos of segyio
gopakumargeetha/DRSA
Deep Recurrent Survival Analysis, an auto-regressive deep model for time-to-event data analysis with censorship handling. An implementation of our AAAI 2019 paper.
gopakumargeetha/opencv
Open Source Computer Vision Library
gopakumargeetha/predict
gopakumargeetha/faultSeg
Using synthetic datasets to train an end-to-end CNN for 3D fault segmentation
gopakumargeetha/volve_eclipse_reservoir
Volve dataset. Reservoir model and simulation results
gopakumargeetha/PageRank
A Python implementation of Larry's famous PageRank algorithm.
gopakumargeetha/ltr-demo
A simple LTR Demo
gopakumargeetha/introtodeeplearning_labs
Lab Materials for MIT 6.S191: Introduction to Deep Learning
gopakumargeetha/jupyter2slides
Cloud Native Presentation Slides with Jupyter Notebook + Reveal.js
gopakumargeetha/bayesian-neural-network-mnist
Bayesian neural network using Pyro and PyTorch on MNIST dataset
gopakumargeetha/ML_well_log
The code describes how unsupervised ML can be applied to well log data for efficient clustering. A part of the well log data is provided.
gopakumargeetha/python-ml-turbofan
gopakumargeetha/Text-Search-Engine
A crappy search engine for text files that I made on one of my many NYC-SF plane flights.
gopakumargeetha/tutorials-1
Tutorials from The Leading Edge column
gopakumargeetha/Plotly-Dashboards-with-Dash
This is the repo for the Udemy Course Python Dashboards with Plotly's Dash
gopakumargeetha/yet_another_tiwtter_sentiment_analysis_part1
gopakumargeetha/handle_imabalnce_class
Address imbalance classes in machine learning projects.
gopakumargeetha/twitter_sentiment_analysis_part11
Twitter sentiment analysis part 11: Word2Vec with Convolutional Neural Network
gopakumargeetha/twitter_sentiment_analysis_part10
Twitter sentiment analysis part 9: Neural Networks with Doc2Vec, Word2Vec, GloVe
gopakumargeetha/twitter_sentiment_analysis_part9
Twitter sentiment analysis part 9: Neural Networks with Tfidf vectors using Keras
gopakumargeetha/twitter_sentiment_analysis_part8
Twitter sentiment analysis part 8: Dimensionality reduction (chi-squared, PCA)
gopakumargeetha/twitter_sentiment_analysis_part2
redefining data-cleaning, preparation for visualisation
gopakumargeetha/twitter_sentiment_analysis_part1
data preparation
gopakumargeetha/imbalanced-data
Notebook implementing techniques discussed in my blog post about imbalanced data.
gopakumargeetha/deep-learning-HAR
Convolutional and LSTM networks to classify human activity