christan's repositories
Multi-Label-Text-classification-Using-BERT
Multi Label text classification using bert
Twitter-Sentiment-Analysis
It is a Natural Language Processing Problem where Sentiment Analysis is done by Classifying the Positive tweets from negative tweets by machine learning models for classification, text mining, text analysis, data analysis and data visualization
Fast-Pytorch
Pytorch Tutorial, Pytorch with Google Colab, Pytorch Implementations: CNN, RNN, DCGAN, Transfer Learning, Chatbot, Pytorch Sample Codes
Smart-Meter-Data-Analytics
A Predictive Analytics Problem Statement to forecast future Electricity Consumption using Household Power Consumption Dataset
Deep-Learning-for-Medical-Applications
Deep Learning Papers on Medical Image Analysis
Text-Classification
Text Classification through CNN, RNN & HAN using Keras
DL4NLP
Deep Learning for NLP resources
awesome-text-summarization-2
Text summarization starting from scratch.
LSTM-Attention-based-Generative-Chat-bot
Personified Generative Chatbot using RNNs (LSTM) & Attention in TensorFlow
Introduction-to-Time-Series-forecasting-Python
Introduction to time series preprocessing and forecasting in Python using AR, MA, ARMA, ARIMA, SARIMA and Prophet model with forecast evaluation.
CHAT-BOT-using-Attention
Chatbot built using RNN Encoder and Decoder with attention mechanism
Bidirectiona-LSTM-for-text-summarization-
A bidirectional encoder-decoder LSTM neural network is trained for text summarization on the cnn/dailymail dataset. (MIT808 project)
detect_facial_keypoints
a computer vision project to recognize facial keypoints
Multi-Label-Text-Classification
Kaggle Toxic Comments Challenge
RL-Chatbot
🤖 Deep Reinforcement Learning Chatbot
Chatbot
In this project, we will build a chatbot using conversations from Cornell University's Movie Dialogue Corpus. The main features of our model are LSTM cells, a bidirectional dynamic RNN, and decoders with attention. The conversations will be cleaned rather extensively to help the model to produce better responses. As part of the cleaning process, punctuation will be removed, rare words will be replaced with "UNK" (our "unknown" token), longer sentences will not be used, and all letters will be in the lowercase. With a larger amount of data, it would be more practical to keep features, such as punctuation. However, I am using FloydHub's GPU services and I don't want to get carried away with too training for too long.
natural-language-processing
Programming Assignments and Lectures for Stanford's CS 224: Natural Language Processing with Deep Learning
ml-fraud-detection
Credit card fraud detection through logistic regression, k-means, and deep learning.
practical_seq2seq
A simple, minimal wrapper for tensorflow's seq2seq module, for experimenting with datasets rapidly
music-generation-with-DL
Resources on Music Generation with Deep Learning
DL-for-Chatbot
Deep Learning / NLP tutorial for Chatbot Developers
awesome-machine-learning
A curated list of awesome Machine Learning frameworks, libraries and software.
Reuters-21578-Classification
Text classification with Reuters-21578 datasets using Gensim Word2Vec and Keras LSTM
Deep-learning-object-detection-links.
Object detectors based on DL (from: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html )
applied-deep-learning-resources
A collection of research articles, blog posts, slides and code snippets about deep learning in applied settings.