Pinned Repositories
A-Flask-Web-App-for-automatic-text-summarization-using-SBERT
We will build a Flask web app that can input any long piece of information such as a blog or news article and summarize it into just five lines! Text summarization is an NLP(Natural Language Processing) task. SBERT(Sentence-BERT) has been used to achieve the same.
Bean-plant-disease-detection-and-classification-Mobilenet-TL
Given an image of a bean plant,the MobileNet model detects the disease and further classifies it.There are 3 categories-healthy,angular leaf spot disease and bean rust disease.The image should be uploaded in the Streamlit web app to view the output.
Face-Mask-Detection-and-Masked-Face-Recognition-Organization
The project uses Computer Vision and Deep Learning to detect if an individual entering the organization is masked or not using CNN on the given video input. If not masked, mail a pandemic alert along with the individual’s photo to the security using SMTP.If masked, recognize the masked individual through image subtraction. Mail an organization alert to the security along with the individual’s photo using SMTP if the masked individual is not an employee of the organization.
Generating-n-grams-in-Python-for-NLP
What are n-grams and how to implement them in Python?
Identification-of-COVID-19-using-CT-scan
Lets build a CNN model from scratch for a multi-class classification problem and identify if a given chest CT scan image is that of COVID-19,healthy or other pulmonary disorders.
matrix.h
matrix.h is a header file to help us perform common matrix operations in our program.Just include this one header file in one's program and one can successfully perform various interesting and useful matrix operations.
My-ML-projects
Own-Mailing-App
Why use GMail when you can create your own mailing app using SMTP in Python!!!The project uses Streamlit front-end which inputs the recipient's address(es),subject-line ,body of the mail and image attachments(if any) and mails just perfectly to the recipient(s).
Three-Address-Code-Generator-App
Compiler Design and System Software project to generate three address code for a given arithmetic equation.Stack data structure and OOps concepts have been employed to implement the same.The project code is in Python for back-end and Tkinter for the front-end.
VGG-19-for-Rock-Paper-and-Scissors-classification
I have built a VGG-19 model to classify hand gestures of rock, paper and scissors using a Kaggle dataset.
Nithyashree-2022's Repositories
Nithyashree-2022/A-Flask-Web-App-for-automatic-text-summarization-using-SBERT
We will build a Flask web app that can input any long piece of information such as a blog or news article and summarize it into just five lines! Text summarization is an NLP(Natural Language Processing) task. SBERT(Sentence-BERT) has been used to achieve the same.
Nithyashree-2022/VGG-19-for-Rock-Paper-and-Scissors-classification
I have built a VGG-19 model to classify hand gestures of rock, paper and scissors using a Kaggle dataset.
Nithyashree-2022/Identification-of-COVID-19-using-CT-scan
Lets build a CNN model from scratch for a multi-class classification problem and identify if a given chest CT scan image is that of COVID-19,healthy or other pulmonary disorders.
Nithyashree-2022/Generating-n-grams-in-Python-for-NLP
What are n-grams and how to implement them in Python?
Nithyashree-2022/Image-Classification-using-Machine-learning
Image classification using four popular machine learning algorithms namely, Random Forest Classifier, KNN, Decision Tree Classifier, and Naive Bayes classifier for CIFAR-10 dataset.
Nithyashree-2022/Shopping-Mall-Management-System
Code in C++ for shopping mall management system OOPs mini-project
Nithyashree-2022/A-Hands-on-introduction-to-Reinforcement-Learning-RL-with-Python
We will get introduced to reinforcement learning and also implement a simple example of the same in Python. It will be a basic code to demonstrate the working of an RL algorithm. Brief exposure to object-oriented programming in Python, machine learning, or deep learning will also be a plus point.
Nithyashree-2022/Face-Mask-Detection-and-Masked-Face-Recognition-Organization
The project uses Computer Vision and Deep Learning to detect if an individual entering the organization is masked or not using CNN on the given video input. If not masked, mail a pandemic alert along with the individual’s photo to the security using SMTP.If masked, recognize the masked individual through image subtraction. Mail an organization alert to the security along with the individual’s photo using SMTP if the masked individual is not an employee of the organization.
Nithyashree-2022/Hyperparameter-optimization-Techniques
A detailed hands-on discussion on the following hyperparameter tuning techniques and decide which is the best for a given dataset
Nithyashree-2022/15-puzzle-problem-
15-puzzle problem is solved using LCBB strategy and general tree data structure
Nithyashree-2022/Bean-plant-disease-detection-and-classification-Mobilenet-TL
Given an image of a bean plant,the MobileNet model detects the disease and further classifies it.There are 3 categories-healthy,angular leaf spot disease and bean rust disease.The image should be uploaded in the Streamlit web app to view the output.
Nithyashree-2022/Blog-Web-App
The project is a personal blog website for a writer.It allows the writer to post new articles,create new categories of articles,add information about their events and books.
Nithyashree-2022/CV
Nithyashree-2022/cv-using-css
I developed my own website using CSS.
Nithyashree-2022/Disk-Scheduling
FCFS and FCLS disk scheduling algorithms were implemented using stack and queue data structures respectively.Both stack and queue are implemented using singly linked lists.
Nithyashree-2022/E-Slate
A digit recognizer Streamlit Web App to recognize the digit drawn lively with Streamlit Canvas .The digit recognizer ANN model can classify the drawn digit which is from 0 to 9.
Nithyashree-2022/mobilenet-tl
Check the Demo here
Nithyashree-2022/My-AI-projects
Nithyashree-2022/My-Data-Science-Projects
Nithyashree-2022/My-ML-projects
Nithyashree-2022/Own-Mailing-App
Why use GMail when you can create your own mailing app using SMTP in Python!!!The project uses Streamlit front-end which inputs the recipient's address(es),subject-line ,body of the mail and image attachments(if any) and mails just perfectly to the recipient(s).
Nithyashree-2022/panda-practice
Nithyashree-2022/Python-programs
Basics of AI
Nithyashree-2022/Three-Address-Code-Generator-App
Compiler Design and System Software project to generate three address code for a given arithmetic equation.Stack data structure and OOps concepts have been employed to implement the same.The project code is in Python for back-end and Tkinter for the front-end.
Nithyashree-2022/Transliterator-for-Indian-languages
Given a text in an Indian language,it will be transliterated to another language which you are more comfortable reading.This is a streamlit web app.
Nithyashree-2022/matrix.h
matrix.h is a header file to help us perform common matrix operations in our program.Just include this one header file in one's program and one can successfully perform various interesting and useful matrix operations.
Nithyashree-2022/Detection-of-Pneumothorax-from-chest-X-ray
Implement image classification for a binary classification problem by building a CNN model from scratch in Python
Nithyashree-2022/How-to-choose-the-best-Machine-Learning-algorithm-for-your-problem-statement-
Keeping healthcare problems in mind, we must hence look for models which are able to detect the disease as much as possible. In this article, let us learn how to accomplish the same. We will be working on the healthcare problem statement of predicting heart failure given the patient's details, building three relevant Machine Learning models, obtaining their confusion matrices, and comparing their performances in order to finalize the best model.
Nithyashree-2022/twitter-sentiment-analysis-bert
Sentiment analysis of tweets from 2016 Presidential elections
Nithyashree-2022/Working-with-directories-using-Python
Imagine a situation where your dataset consists of 1000s of images stored and organized in a directory.How will you pre-process them and finally train your CNN or YOLO model or anything similar???How would you manage to get this data as easily as possible for your project??? You can,of course,upload the folder of images to your drive and make use of the following tips which I exclusively used for some of my projects recently. Manipulating text file content will be very useful to convert files from XML format to YOLO format.