archowdhury Goto Github PK

artificial-neural-networks-ann-using-python

We will use "Keras" to create an Artificial Neural Network in Python and predict the Customer Churn

artificial-neural-networks-using-r-h2o-package-

We will use the "H2O" package to create an Artificial Neural Network in R

bagging-boosting-and-stacking-using-r

Bagging, Boosting and Stacking models using the "caret" package in R

bigmart-sales---testing-various-regression-models

comparing-the-different-types-of-regression

Comparing the different types of Regression

computer-vision---detecting-objects-in-images

customer-churn-prediction-using-neural-networks

This project demonstrates how to use Artificial Neural Networks (ANNs) using Keras/Tensorflow in Python to predict customer churn

demand-forecasting-using-lstm

We need to predict the electricity consuumption of a household with a one-minute sampling rate based on the past 4 years of consumption This is from a Kaggle competition.

extracting-information-from-pdf-files-using-ocr-and-nlp

Extracting relevant information like invoice number, date, amount etc. from PDF files using OCR and NLP techniques

finding-similar-geological-images-using-convolutional-neural-networks

A geology research company wants to create a tool for identifying interesting patterns in their imagery data. They will provide an image of interest and the ML model should return the top "N" similar images

forecasting-demand-for-multiple-products-using-prophet-and-lstm

Forecasting demand using Prophet and LSTM

gradient-boosting-using-python-xgboost-

This project demonstrates how to use XGBoost to predict customer churn. It also shows how to do hyperparameter tuning.

knn-to-classify-fruits

In this mini-project we will compare the results using KNN classification directly versus using the Caret package

language-translation-using-seq2seq-models

loan-prediction-using-the-caret-package

This project aims at predicting the customers likely to default on a Loan

locating-the-heart-in-x-ray-images-using-pytorch-and-resnet18

machine-learning

Content for Udacity's Machine Learning curriculum

named-entity-recognition-ner-using-deep-learning

Named-entity recognition (NER) is also known as entity identification, entity chunking and entity extraction. The objective is to identify entities like person names, organizations, locations etc. from unstructured text.

neural_machine_translation

opencv

Open Source Computer Vision Library

parameter-efficient-fine-tuning-llms-with-qlora

In this project we will train the Phi2 LLM model from Microsoft on custom data using QLoRA.

partitioning-around-medoids-pam-using-r

This project demonstrates how to use the "Partitioning Around Medoids" (PAM) technique to create clusters

predicting-car-prices

This project involves predicting car prices in the secondary market. It's a simple exercise on data cleaning and the predicting the price using Random Forests

predicting-pneumonia-from-x-ray-images

principal-component-analysis-pca-and-svm-using-r

question_answering_using_transformers

recommender-engines-using-spark-als

This project demonstrates how to build a Recommender Engine for recommending musical instrument purchases using Spark ALS. The data for this has been taken from actual Amazon product reviews

semantic_segmentation

Semantic Segmentation

sentiment-analysis-using-bert-and-pytorch

sentiment-classification-of-amazon-product-reviews-using-spacy