snehachikhalekar Goto Github PK

ai_deeplearning_ann_mlp_tuned

Using MLP (AI - ANN), identify products at risk of backorder before the event occurs so that business has time to react.

autoencoders

Implementing a simple neural network based and a convolutional autoencoder using tensorflow

autoencoders-simple-regularized-deep-

It gives the implemention of simple autoencoder, regularized autoencoder (uisng L1 feature selection) and deep autoencoder on MNIST dataset

automatic-image-captioning

Generating Captions for images using Deep Learning

basics_deeplearning

Multilayer Perceptron Model on Classification Problem

basics_kmeansclustering

This is simple and basic clustering example I tried on Kaggle Dataset wherein I also do many visualization on features to know the patterns and finally made clusters out of them

binaryclassification-autoencoder-deep-learning-

BinaryClassification uisng preprocessing step of Autoencoder (Deep Learning)

convolutional_neural_networks_with_keras

Building a CNN from scratch in keras using tensorflow backend

custom_function

deep_learning_using_pytorch

How to build Neural Networks using PyTorch

distracted-driver-detection

Driver distraction detection to reduce the accidents

linearregression

Linear-Regression_for_Grade_Prediction

lstm-human-activity-recognition

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN (Deep Learning algo). Classifying the type of movement amongst six activity categories - Guillaume Chevalier

lstm_rnn_tutorials_with_demo

LSTM-RNN Tutorial with LSTM and RNN Tutorial with Demo with Demo Projects such as Stock/Bitcoin Time Series Prediction, Sentiment Analysis, Music Generation using Keras-Tensorflow

pytorch-tutorial

PyTorch Tutorial for Deep Learning Researchers

regularizer-batch-normalizer-and-dropout-

Basic regularization techniques in MLP Batch Normalization and Dropout

rnn_lstm_from_scratch

How to build a RNN and LSTM from scratch with NumPy.

scarping-sample

Basics of Scarping wherein I have mentioned basics methods used for the same with some examples. I have pick up the examples from shopping site and Youtube vidoes

scrapingdata

Code for getting data from social media for your data science projects!

sentimentanalysis

Sentiment Analysis on Women Reviews on Clothing (Dataset from Kaggle)

sentimentanalysis-

Sentiment analysis on the fandom site mentioned in the notebook wherein I have made analysis on the Sentiment of the quotes gathered which are popular dialogues by the actors of Naruto

sentimentanalysis_twittersampledata

Some basic cleaning and analysis of Tweets gathered using Twitter API and doing Sentiment Analysis using TextBlob

text_classification_rnn_and_cnn

Binary and tertiary class classification using RNN and CNN respectively.

textanalysis-

Text Analysis (Sentiment Analysis) I referred problem solved on Text Mining on the 2019 Mexican Government Report, covering from extracting text from a PDF file to plotting the results

uisng-spacy-text-analysis-

using_spacy_textanalysis

I have done basic text analysis on Avengers ( Infinity war reviews). Where in I have scrape the data from site mentioned in the file and analyzed the similarity in the dialogues of the characters and the nouns and verbs used by them

word_embeddings_in_keras