Create a voice cloning application using deep learning, with steps for data preparation, model training, and voice inference to generate realistic and customizable voice clones.

Voice Cloning Application Using RVC

Automatic Eye Cataract Detection is an AI-based tool leveraging YOLOv8 for precise and quick cataract diagnosis, enhancing efficiency and accuracy in eye care.

Automatic Eye Cataract Detection Using YOLOv8

This project utilizes YOLOv8 to build a crop disease detection and classification system in Google Colab. The system processes images and videos to identify diseases, providing an interactive interface for real-time analysis using Gradio.

Crop Disease Detection Using YOLOv8

This tutorial on Vegetable Classification using Machine Learing, guides you through automating the sorting process, improving quality control, and enhancing efficiency in agriculture and food industries.

Vegetable classification with Parallel CNN model

Banana Leaf Disease Detection leverages Deep Learning and Computer Vision to identify plant diseases early, helping farmers protect their crops, improve cultivation, and reduce losses with smarter, more sustainable farming methods.

Banana Leaf Disease Detection using Vision Transformer model

Our project uses deep learning to detect leaf diseases from images. By training models like VGG16 and EfficientNet on a robust dataset, we accurately diagnose plant conditions, aiding farmers in early disease detection and promoting healthier crops.

Leaf Disease Detection Using Deep Learning

Glaucoma Detection Using Deep Learning uses AI to find early signs of glaucoma in eye images. This helps doctors diagnose the disease quickly and prevent vision loss.

Glaucoma Detection Using Deep Learning

Our Blood Cell Classification project uses CNN, EfficientNetB4, and VGG16 models to correctly sort blood cell images. This reduces up and improves the accuracy of research, which helps doctors make better decisions.

Blood Cell Classification Using Deep Learning

Skin Cancer Detection project leverages advanced deep learning models, including CNN, DenseNet121, and EfficientNetB4, to accurately classify skin cancer images. This initiative aims to improve early diagnosis and patient outcomes.

Skin Cancer Detection Using Deep Learning

Our Cervical Cancer Analysis project leverages the power of EfficientNetB0 to accurately classify different types of cervical cells. This initiative aims to enhance early cancer detection and improve patient outcomes through advanced AI technology.

Cervical Cancer Detection Using Deep Learning

Get a complete overview of Generative AI, covering models, use cases, benefits, limitations, tools, ethics, and industry applications.

Nutritionist Generative AI Doctor using Gemini

Create advanced chatbots and AI projects with GPT-3.5-turbo and GPT-4. Perfect the art of designing human-like interactions using detailed code examples.

Chatbots with Generative AI Models

This project builds an XGBoost Regressor to predict healthcare costs, ensuring insurance profitability. We'll compare it with a linear regression baseline and learn to communicate results effectively to non-technical stakeholders.

Insurance Pricing Forecast Using XGBoost Regressor

This project shows how analytics and AI increase profit and reduce risk in player selection by using linear regression to predict performance for British Premier League football stars.

Linear Regression Modeling for Soccer Player Performance Prediction in the EPL

Learn to build real-time image classification models using Convolutional Neural Networks (CNN). This tutorial will guide you through creating and training models to predict insights for AI projects,

Complete CNN Image Classification Models for Real Time Prediction

This project teaches Deep Neural Networks (DNNs) using a dataset of 86,000 businesses. Participants will learn key concepts and use Python libraries like pandas, numpy, and TensorFlow for data analysis, cleaning, model building, and tuning.

Predictive Analytics on Business License Data Using Deep Learning

Diffusers and stable diffusion models can be used to improve image production. This project enables realistic synthesis with advanced deep learning techniques, interactive image creation via Gradio UI, and customizable training.

Image Generation Model Fine Tuning With Diffusers Models

Question Answering system built on Pegasus+SQuAD for accurate responses. Optimized for high accuracy and user experience across applications

Question Answer System Training With Distilbert Base Uncased

The Semantic Search System with Transformers and Faiss vectors can speed up and improve the accuracy of your searches. Find out about advanced information retrieval and personalized suggestions for a wide range of businesses.

Semantic Search Using Msmarco Distilbert Base & Faiss Vector Database

Advanced transformer models and tokenization methods can be used to automate the summarization of documents. Quickly make high-quality abstracts to help people find knowledge and make decisions.

Document Summarization Using Sentencepiece Transformers

The goal of this project is to create a customer support chatbot by using advanced methods for natural language processing.

Customer Service Chatbot Using LLMs

YOLOv8 is used in this project to identify human poses in real time. As the COCO dataset is used to train the model, its performance is checked, and poses in photos and videos are predicted. Pose recognition compresses the video output so that it can be s

Real-Time Human Pose Detection With YOLOv8 Models

YOLOv8 and OCR models are used for accurate and quick results in automated license plate identification and recognition.

Real-Time License Plate Detection Using YOLOv8 and OCR Model

You can improve UNet training by using checkpoints, LR adjustments, label encoding, and seeing examples to make sure they work.

Medical Image Segmentation With UNET

AI Automated Insights

InferKit

Article Forge

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Android Authority

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TinyWow

Nichesss AI

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Vondy

[Solved] OpenAI Python Package Error: 'ChatCompletion' object is...

[Solved] OpenAI Python Package Error: 'ChatCompletion' object is not subscriptable

[Solved] OpenAI API error: "The api_key client option must be set...

[Solved] OpenAI API error: "The api_key client option must be set either by passing api_key to the client or by setting the OPENAI_API_KEY env variable"