All current Gradient Descent Courses courses in 2024

24 Courses

Neural Networks Basics from Scratch

Embark on an in-depth exploration of Neural Networks and their pivotal role in modern AI with our comprehensive course. Gain hands-on experience by manually implementing foundational AI tools such as Perceptrons, activation functions, and the integral components of multi-layer Neural Networks. Delve into the core mechanisms without relying o.
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How Neural Networks Learn: Exploring Architecture, Gradient Descent, and Backpropagation

How Neural Networks Learn: Exploring Architecture, Gradient Descent, and Backpropagation Neural networks drive many artificial intelligence applications today. This course will teach you what’s behind the magic—the dynamics of training neural networks, including backpropagation, gradient descent, and how to optimize network performance. So, you.
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Yapay Zeka ve Derin Öğrenme A-Z™: Tensorflow

Yapay Zeka ve Derin Öğrenme A-Z™: Tensorflow Google Tensorflow ile Python dilinde makine öğrenimi, yapay sinir ağları ve deep learning programları geliştirin. Bu kapsamlı kurs, Udemy tarafından sunulmaktadır ve meraklılarına derin öğrenme ve makine öğrenimi alanında güçlü bir temel sağlayacaktır. Üniversite: Udemy Kategoriler: Python.
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provider Udemy
pricing Paid Course
duration 7 hours
sessions On-Demand

Deep Learning: Recurrent Neural Networks with Python

Deep Learning: Recurrent Neural Networks with Python With the exponential growth of user-generated data, mastering RNNs is essential for deep learning engineers to perform tasks like classification and prediction. Architectures such as RNNs, GRUs, and LSTMs are top choices, making mastering RNNs a priority. This course starts with the basics an.
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RNN Architecture and Sentiment Classification

Title: RNN Architecture and Sentiment Classification Description: Artificial Intelligence is revolutionizing data analysis. This course delves into Recurrent Neural Networks (RNNs), starting with basic memory models and advancing to deep RNN structures. You'll explore RNN models like ManyToMany, ManyToOne, and OneToMany through practical exerci.
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Introduction to RNN and DNN

Introduction to RNN and DNN Artificial Intelligence is transforming industries by enabling machines to learn from data and make intelligent decisions. This course offers an in-depth exploration of Recurrent Neural Networks (RNN) and Deep Neural Networks (DNN), two pivotal AI technologies. You’ll start with the basics of RNNs and.
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人工智能与医学数据计算

《人工智能与医学数据计算》课程共分为十节课。课程从人工智能与医学数据计算的背景知识入手,提供人工智能和深度学习的发展概述。第二课分析人工智能目标,介绍关键技术及相关概念,重点解析两种不同人工智能技术的区别与联系。 第三和第四节课概述人工智能的基本应用场景及操作环境的软硬件要求,为后续的深度学习关键技术学习奠定基础。第五节课关注深度学习网络架构,.
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Neural Networks in Python from Scratch: Complete guide

Embark on a complete journey to understand neural networks with our course "Neural Networks in Python from Scratch." Dive into the world of Deep Learning, learning to build neural networks with Python from the ground up. Gain insights into both theory and hands-on practice, providing you with a robust understanding of deep learning methodol.
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Introduction to Neural Networks with PyTorch

Learn the fundamentals of neural networks with Python and PyTorch, and then use your new skills to create your own image classifier—an application that will first train a deep learning model on a dataset of images and then use the trained model to classify new images. University: Udacity Provider: Udacity Python Courses Computer Vision.
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provider Udacity
pricing Paid Course
duration 4 weeks, 4-5 hours a week
sessions On-Demand
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