Architectshwet

Amazon-Fine-Food-Reviews

Sentiment Analysis on Amazon Fine Food Reviews Data in Python

Chatbot_csv_gpt3

GPT-3 based chatbot on the tabular data developed using langchain, openai, streamlit and FAISS as a vector database

Customer-churn-prediction

A project about building a stacked model with tuning the hyperparameters with grid search and hyperopt and used PySpark to test the performance of model in Spark Clusters in AWS EC2 and ROSE to balance the target variable

Deployed-multiple-Transformers-models-using-Amazon-SageMaker-Multi-Model-Endpoints

Flower-species-Recognition-using-Computer-vision-and-Machine-Learning

Used Convolutional Deep Neural nets to extract features from the image

Kaggle-Bike-Sharing-Demand-Challenge-

Predictive Analysis on Kaggle Bike Sharing Demand Challenge data in Python

Loan-prediction-using-Machine-Learning-and-Python

To design a predictive model using xgboost and voting ensembling techniques and extract insights from the data using pandas, seaborn and matplotlib

Recommendation-algorithms-in-Python-

A project about implementation of content based, memory & model based collaborative and deep learning models for building Recommendation engine

Text-Classification-using-BERT

Train-on-Amazon-SageMaker-using-spot-instances

Architectshwet/Loan-prediction-using-Machine-Learning-and-Python

To design a predictive model using xgboost and voting ensembling techniques and extract insights from the data using pandas, seaborn and matplotlib

Architectshwet/Flower-species-Recognition-using-Computer-vision-and-Machine-Learning

Used Convolutional Deep Neural nets to extract features from the image

Architectshwet/Amazon-Fine-Food-Reviews

Sentiment Analysis on Amazon Fine Food Reviews Data in Python

Architectshwet/Customer-churn-prediction

A project about building a stacked model with tuning the hyperparameters with grid search and hyperopt and used PySpark to test the performance of model in Spark Clusters in AWS EC2 and ROSE to balance the target variable

Architectshwet/Deep-Learning-modules-in-Keras

A project about the brief implementation of MLP, CNN, RNN, Unsupervised learning with Autoencoders, ETC, Text analytics using CNN in Python

Architectshwet/Deployed-multiple-Transformers-models-using-Amazon-SageMaker-Multi-Model-Endpoints

Architectshwet/Final-Year-Project-CED15I027-

Architectshwet/Mushroom-Classification

Data science project on mushroom classification data

Architectshwet/Text-classification-sarcastic-or-not

Text mining and Data Science applications on the twitter-data

Architectshwet/Text-Mining-Heathcare

A project about the brief application of tm & qdap libraries to clean the text data by forming corpus followed by applying dtm and further sparsity and designed a stacked model of random forest, gradient boost, xgboost & deeplearning by using h2o library for Machine Learning

Architectshwet/Toxic-Comment-Classification

A NLP project about a brief application of tfidf vectorizer for text feature extraction and pipeline and feature union to chain multiple steps into one

Architectshwet/Chatbot_csv_gpt3

GPT-3 based chatbot on the tabular data developed using langchain, openai, streamlit and FAISS as a vector database

Architectshwet/Recommendation-algorithms-in-Python-

A project about implementation of content based, memory & model based collaborative and deep learning models for building Recommendation engine

Architectshwet/Text-Classification-using-BERT

Architectshwet/Train-on-Amazon-SageMaker-using-spot-instances

Architectshwet/APMC-Mandi-Machine-Learning

A time series forecasting project about the brief application of lstm(deep learning), prophet, arima, holt, exponential smoothing algorithms

Architectshwet/Black-Friday

Predictive Analysis on Black Friday Data in Python

Architectshwet/Classifying-duplicate-questions-from-Quora-with-Keras

Classifying-duplicate-questions-from-Quora-with-Keras

Architectshwet/Credit-Fraud-Detection-using-Autoencoder-and-keras

Credit-Fraud-Detection-using-Autoencoder-and-keras

Architectshwet/dvc-ml

Architectshwet/Felicity-Kings-of-machine-learning--Analytics-vidhya

Data science project on Dota game stats data

Architectshwet/Implementation-of-different-Machine-Learning-algorithms-from-scratch-in-Python

Depth analysis on how to develop a machine learning algorithm from scratch in python. Algorithms covered are linear regression, logistic regression, decision trees, knn, k-means clustering.

Architectshwet/Judiciary-dataset-challenge

Architectshwet/Kaggle-data-science-survey-data-analysis-using-shiny-web-app-in-R

A data analytics project for analyzing and studying the data collected by the Kaggle from its Data science survey conducted in 2017 to understand and explore various trends in Data science industry and how interested people are in this buzz word

Architectshwet/Machine-Learning-modules

Implementation of different python modules for data preprocessing, classification, regression, NLP and recommendation engine algorithms

Architectshwet/Porto-seguro-data

A brief application of xgboost (with tuning the parameters with caret) algorithm and ROSE library to balance the target variable

Architectshwet/Recruit-Restaurant-Visitor-Forecasting-

Time Series Analysis & Forecasting of Restaurant visitor. EDA, Forecasting with Prophet, arima and h2o auto ml for regression.

Architectshwet/Statistical-Learning-using-R

Statistical Learning application of different machine learning algorithms on dataset and their implementation in R covering model selection techniques, shrinkage Methods and Regularization techniques, different non linear models, re-sampling methods and Cross Validation, boosting, trees, supervised learning & Unsupervised learning

Architectshwet/Student-grade-prediction-and-alcohol-consumption-

A project which aims at finding the factors and most important features which lead to students indulging in drinking and consuming alcohol.After the exploratory data analysis a decision tree is trained and inference rules are generated to predict which student is most likely to consume alcohol and its grade

Architectshwet/Uber-Data

A project about the brief application of highcharter, dplyr & lubridate library to preprocess, mainipulate and visualize data in R.