Implementation of End to End Kaggle Machine Learning Project With Deployment
Comprehensive guide to implementing a machine learning project for car price prediction, covering data exploration, model fitting, and deployment on Heroku.
Convolutional Neural Networks
Explore convolutional neural networks for computer vision, covering feature extraction, network architecture, and real-world applications like self-driving cars in this comprehensive lecture.
Convolutional Neural Networks
Explore convolutional neural networks for computer vision tasks, covering feature extraction, convolution operations, and applications in classification, segmentation, and image captioning.
LLMOps: Personalizar ViT Classifier con tu Propia Data y Docker Inference
Personaliza un Vision Transformer con tu dataset, crea un docker y un punto de inferencia con FastAPI para clasificación de imágenes.
Fundamentals and Trends in Vision and Image Processing - Aula 32
Explore fundamentos e tendências em processamento de visão e imagem, aprofundando conhecimentos avançados em técnicas e aplicações da área.
Machine Learning for Time Series
Odkryj techniki uczenia maszynowego do analizy szeregów czasowych. Poznaj metody prognozowania i identyfikacji wzorców w danych sekwencyjnych.
Fundamentals and Trends in Vision and Image Processing - Aula 36
Explore fundamentos e tendências em processamento de visão e imagem, aprofundando conhecimentos avançados em técnicas e aplicações da área.
Fundamentals and Trends in Vision and Image Processing - Aula 31
Explore fundamentos e tendências em processamento de visão e imagem nesta aula de mestrado, abordando conceitos avançados e aplicações práticas na área.
Fundamentals and Trends in Vision and Image Processing - Aula 28
Explore fundamentos e tendências em processamento de visão e imagem, aprofundando conhecimentos avançados em técnicas e aplicações da área.
Fundamentals and Trends in Vision and Image Processing - Aula 27
Explore fundamentos e tendências em processamento de visão e imagem, aprofundando conhecimentos avançados em técnicas e aplicações da área.
How to Use Satellite Imagery to Be a Machine - Sean Patrick Gorman, PhD | ODSC West 2018
Explore satellite imagery analysis using Jupyter notebooks, learn to extract valuable information, and develop ML models for processing Earth observation data.
Audio Processing in Python with Feature Extraction for Machine Learning
Learn audio processing in Python using librosa for feature extraction, beat detection, and spectral analysis. Explore practical techniques for music information retrieval and machine learning applications.
Exploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound
Explore automatic COVID-19 diagnosis using crowdsourced respiratory sounds. Learn about data collection, symptom correlation, and detection techniques in this cutting-edge research presentation.
Big Data in Cybersecurity
Explore big data's role in cybersecurity, covering classification, feature extraction, and cheat detection. Learn innovative frameworks and future trends in this field.
Cyber & Data - Introduction to Splunk and Machine Learning
Explore Splunk and machine learning techniques for data analysis, including anomaly detection, prediction, clustering, feature extraction, and preprocessing methods.
Advanced Anomaly Detection Made Easy
Advanced anomaly detection techniques for embedded ML, focusing on custom DSP blocks, feature importance, and threshold optimization. Learn to implement these methods for various IoT applications using Edge Impulse.
Unsupervised Features Learning for Sampled Vector Fields
Explore innovative techniques for analyzing sampled vector fields using graph structures and unsupervised learning, revealing hidden features correlated with known dynamics in analytical models.
The AI of Where - Unleashing the Power of GenAI on Geospatial Data
Explore cutting-edge GenAI applications in location intelligence, enhancing spatial data analysis. Learn innovative uses of Large Language Models and Segment Anything Model for geospatial datasets, with real-world examples and case studies.
Low Rank Tensor Completion and Its Applications
Explore low rank tensor completion methods using framelet, dictionary coding, deep plug-and-play prior, and more. Gain insights into theoretical and numerical results for solving complex imaging problems.
In-Database Factorised Learning - Professor Dan Olteanu
Explore in-database factorised learning techniques for efficient data analysis and machine learning, covering integration approaches, advantages, and practical applications in relational databases.
A Brief Introduction to Photogrammetry - Rust CV Meeting 2021
Explore photogrammetry basics, including pinhole cameras, feature extraction, and 3D model creation. Learn key concepts and techniques for computer vision applications.