Gangadhar k's Projects
Beginner deep learning projects with Python, TensorFlow, and Keras. Learn to build and train neural networks to solve real-world problems.
BirdClassifier is a deep learning model designed to identify various bird species accurately. It leverages cutting-edge technology, integrating MobileNet-v2 and Convolutional Neural Network (CNN) architectures. MobileNet-v2 is chosen for its lightweight and efficient design, making it ideal for mobile applications.
CRISP is a cutting-edge React-based admin panel designed specifically for managing and optimizing university bus tracking systems. With a focus on enhancing passenger experience and providing real-time route information, CRISP empowers university administrators to efficiently oversee and monitor the entire transportation network.
https://gangadhar24377.github.io/Gangadhar---21BCE7658/index3.html
React Invoice Generator is a user-friendly web application that enables users to effortlessly create professional invoices. With a sleek and intuitive interface, it empowers businesses and freelancers to streamline their invoicing process. Customize templates, calculate totals, and generate PDFs for easy sharing. Boost your productivity today!
Legit Java Basics like from Zero
An interactive mongodb based chatbot
Monocular depth estimation utilizes Unet architecture, a neural network model. Unet encodes image features and decodes them to predict depth from single images. It's crucial for applications like autonomous driving and augmented reality
Predict customer churn using Artificial Neural Network (ANN) for better business insights.
U heard, its python for AIDS
Python Basics and Projs
Project goal: Develop an ML model to predict tags for Stack Overflow questions, streamlining answers and expert discovery.
Config files for my GitHub profile.
This repository contains the codes of "A Lip Sync Expert Is All You Need for Speech to Lip Generation In the Wild", published at ACM Multimedia 2020.
Wav2Lip-HQ Inference is an advanced Python-based lip-syncing solution, leveraging the powerful Wav2Lip-HQ model to produce high-fidelity talking-face videos. Seamlessly aligning the lip movements of a person in a source video with custom audio, this repository enables the creation of lifelike lip-synced content that captivates viewers.
Yoda uses PyTube and BERT for answering questions based on YouTube video content.