Prajwal Kumar's Projects
Covered some miscellaneous topics, problems and codes to help the learners understand the C language
IBM Python project for data science
Developed an Autism Detection model using Python, Pandas, and Scikit-learn, with data preprocessing, encoding categorical variables, and correlation analysis. Achieved an accuracy of 66% while Implementing logistic regression, XGBoost, and SVM classifiers, achieving an R-squared score of 1.0 for each.
Undertook a comprehensive climate data analysis project to explore and understand historical climate patterns and trends. The objective is to derive valuable insights from climate data, enabling a better understanding of weather conditions over time.
my notes on computational thinking for problem solving
Created a hybrid content-based & segmentation-based technique for resume parsing with unrivaled level of accuracy & efficiency. Provided resume feedback about skills, vocabulary & third-party interpretation, to help job seeker for creating compelling resume.
Developed an NLP-based chatbot using Python3 & Keras, which uses Deep Learning to analyze the user's message, classify it into a broader category and then reply with a suitable note or the required information.
Developed a data analysis project that focuses on understanding and analyzing customer behavior based on transactional data. The goal is to perform Exploratory Data Analysis (EDA) to derive valuable insights into customer preferences, purchasing patterns, and overall behavior.
A short brief on data visualization for new learners.
Developed a Deep Learning-driven Ontology for Precise Medicine Prescription using TensorFlow and rdflib, integrating structured medical data from a CSV file to create an ontology and training a neural network model to predict medicines for given diseases. Demonstrated the system through a client demo video and facilitated code shipment via AnyDesk.
Programmed a Generative AI system using Stable Diffusion with ControlNet image diffusion model, which takes the use of a Hugging Face model and generated designer QR Codes integrated into photos specifies by the user.
Topics covered - Big 'O' notation, merge sort, randomized sort, bubble sort.
Driver drowsiness detection is a car safety technology which helps prevent accidents caused by the driver getting drowsy. Various studies have suggested that around 20% of all road accidents are fatigue-related, up to 50% on certain roads.
Using EVs' charging data, I explored when drivers are likely to plug in their cars, and how much additional electricity demand will be created when the number of EVs increases.
To provide a free service of interaction with a machine, the objective of “Emotionally Aware Chatbot” is to provide mental healthcare to those who are mentally-ill anywhere and anytime. It raises the question of what role, if any, the chatbot should play in suicide prevention.
We will be using the Breast Cancer Dataset and here is a brief context about the same: Breast cancer is a type of cancer that starts in the breast. Cancer starts when cells begin to grow out of control. Breast cancer cells usually form a tumor that can often be seen on an x-ray or felt as a lump. Breast cancer occurs almost entirely in women, but men can get breast cancer, too. A benign tumor is a tumor that does not invade its surrounding tissue or spread around the body. A malignant tumor is a tumor that may invade its surrounding tissue or spread around the body.
google it automation with python professional certificate
A short overview on the Hashing for new beginners
This repository contains all the resources and solution to quizzes given and asked in IBM Data Science Professional Certification.
Google IT Automation with Python Professional Certificate - Practice files
Built an NLP Algorithm to identify the Language of any specific sentence using Bidirectional LSTMs (RNN) model and Fine-Tuned dataset curating over 1000 sentences from 10 different languages, which then achieved an accuracy rate of 98%.
In this I have implemented Logistic regression on Insurance data
In this example, I use data from cancer.gov and the US Census American Community Survey to build a multivariate Ordinary Least Squares regression model. This example is built using Python. It covers: How I sourced and imported the data Preparation of data Exploratory analysis Model selection Model diagnostics Note that this is a first pass attempt and should be considered a baseline model to compare future iterations against.
🧠💬 Articles I wrote about machine learning, archived from MachineCurve.com.
Essential and Fundametal aspects of Natural Language Processing with hands-on examples and case-studies
here I've shared the study material for an important and exceptional course called fundamentals of deep learning offered by nvidia. Please be free to learn from the given slides.
NVIDIA GTC'22 DLI Workshop materials for learners
Embark on a time series analysis project using a dataset with a time component, specifically historical stock prices. The objective is to uncover patterns, trends, and insights from the temporal data, enabling a better understanding of stock price movements over time.
Config files for my GitHub profile.
IBM data science capstone project final presentation
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent