suhasmaddali

Cab-Reservation-System-

🚖 Worked with Cab Reservation system and improved the User Interface. In addition to this, built this system with machine learning capabilities such as accurately predicting the time it takes for the driver to arrive on time.

Car-Prices-Prediction

🚕 Given a set of features such as the car brand, model, year of manufacture and other factors, we would be able to predict the price of the car in the next few years. We would be using different regression models in our process of predicting the prices of cars respectively.

Heart-Disease-Prediction

🫀 We would be using machine learning models to predict the chances of a patient suffering from a heart disease using various features such as cholesterol levels and chest pain type. We would be just considering a sample dataset just to get an understanding of the various machine learning models that could be put to action and learn their implementation. We would also be considering various classification metrics just to compare how well the models did on the test data.

Predicting-Loan-Default-Using-Machine-Learning

Predicting whether someone would pay back their home loan would be really useful especially for banks if they are trying to give loan to a person respectively. Using machine learning and deep learning, we are going to be using the features that are present in our data and we are going to understand the predictions given by the machine learning models respectively.

Predicting-Readability-of-Texts-Using-Machine-Learning

The aim of this project is to predict the difficulty level of the text using various machine learning techniques respectively.

Solar-Panels-Dust-Detection

This repository contains a project on solar panels dust detection using Convolutional Neural Networks (CNNs) architectures and their comparison.

Steel-Defect-Detection-Challenge

🔩 It would be really good if we are to predict the chances of defect occurring in steel so that necessary precautions could be taken during manufacture and during the construction of different sites with steel. In this machine learning project, we are going to be working with images of steel and their annotated examples and understand the defects that are present in steel respectively.

Twitter-Sentiment-Analysis

🙂 Using machine learning techniques and text extraction, we are going to be predicting the sentiment of the text whether it is positive or negative. This ensures that companies save a lot of amount by understanding the sentiment of texts given by users during different instances of time respectively.

Washington-Bike-Demand-Prediction

Using different machine learning and deep learning techniques, the demand for Washington Rental Bikes would be predicted so that the companies could ensure that people receive bikes as and when needed.

Youtube-Video-Analysis

📽 In this problem, we would be analyzing the various trends in youtube which includes views, likes and dislikes. Moreover, we would be plotting visualization plots to understand the trends and make generalizations respectively.

suhasmaddali/Car-Prices-Prediction

🚕 Given a set of features such as the car brand, model, year of manufacture and other factors, we would be able to predict the price of the car in the next few years. We would be using different regression models in our process of predicting the prices of cars respectively.

suhasmaddali/Twitter-Sentiment-Analysis

🙂 Using machine learning techniques and text extraction, we are going to be predicting the sentiment of the text whether it is positive or negative. This ensures that companies save a lot of amount by understanding the sentiment of texts given by users during different instances of time respectively.

suhasmaddali/Predicting-Readability-of-Texts-Using-Machine-Learning

The aim of this project is to predict the difficulty level of the text using various machine learning techniques respectively.

suhasmaddali/Solar-Panels-Dust-Detection

This repository contains a project on solar panels dust detection using Convolutional Neural Networks (CNNs) architectures and their comparison.

suhasmaddali/Steel-Defect-Detection-Challenge

🔩 It would be really good if we are to predict the chances of defect occurring in steel so that necessary precautions could be taken during manufacture and during the construction of different sites with steel. In this machine learning project, we are going to be working with images of steel and their annotated examples and understand the defects that are present in steel respectively.

suhasmaddali/Washington-Bike-Demand-Prediction

Using different machine learning and deep learning techniques, the demand for Washington Rental Bikes would be predicted so that the companies could ensure that people receive bikes as and when needed.

suhasmaddali/English-Language-Learning-Prediction-with-AI-and-Machine-Learning

Artificial intelligence is being used to improve essay writing skills by evaluating student essays. NLP techniques analyze coherence, clarity, and relevance, while topic modeling and sentiment analysis determine main themes and emotional tone. Machine learning algorithms evaluate essays and provide feedback to help students improve their writing.

suhasmaddali/Telco-Customer-Churn-Prediction

This predicts whether a customer is going to churn or not based on the past history of subscriptions.

suhasmaddali/suhasmaddali

This is my GitHub main page that highlights a list of projects, experience and certifications in the field of data science, machine learning, data science and deep learning.

suhasmaddali/Youtube-Video-Analysis

📽 In this problem, we would be analyzing the various trends in youtube which includes views, likes and dislikes. Moreover, we would be plotting visualization plots to understand the trends and make generalizations respectively.

suhasmaddali/Cab-Reservation-System-

🚖 Worked with Cab Reservation system and improved the User Interface. In addition to this, built this system with machine learning capabilities such as accurately predicting the time it takes for the driver to arrive on time.

suhasmaddali/Google-Play-Store-Genre-Prediction

In this repository, machine learning and data science are used to predict the genre of various applications.

suhasmaddali/Wheat-Detection-Using-Computer-Vision

With the help of convolutional neural networks (CNNs), the repository contains code that helps in predicting the chances of wheat having certain types of diseases.

suhasmaddali/MNIST-classification-

MNIST dataset contains images of handwritten digits. With Convoluted Neural Networks, prediction of the digits would be performed.

suhasmaddali/Wheat-Disease-Detection-

It contains code that uses state-of-the-art convolutional neural networks (CNNs) and transfer learning to predict the chances of wheat plants having various types of diseases.

suhasmaddali/Article-Recommender-System

This repository describes various ways of solving data problems with unsupervised machine learning. Clustering based approaches are shown along with other methods. A description of the problem statement is given in the readme file explaining the practical use case of recommendation systems.

suhasmaddali/Certifications

This repository contains a list of all the certifications obtained as a result of completing various courses.

suhasmaddali/Fake-News-Prediction

It contains code that is used to detect the presence of fake news with machine learning and data science.

suhasmaddali/Images

Images that are used in the Git repository are first uploaded in this repository for easy access. Once the images are uploaded in this repository, their links would be accessed for all the other repositories.

suhasmaddali/Resume-

This repository contains a list of all my resumes that could be used for various machine learning related roles.

suhasmaddali/Adare-Restaurant-Webpage

A website is designed with HTML5 and CSS3 to help people book seats in Adare Restaurant. Along with the design, the exact location of the restaurant is also shown so that users get an idea of the exact location of the restaurant.

suhasmaddali/Convoluted-Neural-Networks-CNN-Implementation-Using-Keras

We would be using the convoluted neural networks and plotting the cross validation and the test error of the output. We would be using different structures with different layers on top of each other in order to get different outputs. This project was done in collaboration with appliedAI team based in India.

suhasmaddali/health_assistant

A health assistant application, powered by large language models (LLMs), offers patients the ability to receive preliminary diagnoses for a variety of health issues. It's important to note, however, that these suggestions should be followed up with a consultation from a qualified doctor to ensure accuracy and safety.

suhasmaddali/Roar-Bikes-Webpage

This is a repository that contains a website design for Roar bikes (randomly created name).

suhasmaddali/demand-planner-copilot

suhasmaddali/deploy-streamlit-ec2

suhasmaddali/docker-react

suhasmaddali/html-portfolio

suhasmaddali/legalgpt

suhasmaddali/streamlit_visualization_llm