All current Gradient Descent Courses courses in 2024
22 Courses
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.
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.
Udacity
Paid Course
4 weeks, 4-5 hours a week
On-Demand
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.
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.
Udemy
Paid Course
7 hours
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.
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.
AI Theory and Coding
AI Theory and Coding | CodeSignal
AI Theory and Coding
Provider: CodeSignal
Delve into the fascinating realm of Artificial Intelligence with our comprehensive course. Specifically crafted to equip you with a profound understanding of traditional Machine Learning techniques, our program guides you through implementing key algor.
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，.
小白学人工智能
中国也在大力发展新一代人工智能技术，并致力于将其应用于各行各业。本课程完成后，学生将能够：
了解人工智能行业的最新应用和发展趋势。
从数据、算法和计算力的角度理解人工智能的发展。
用行业或生活术语比喻人工智能的概念和原理。
体验和理解深度学习原理，涉及CNN、图像风格迁移、RNN等架构。
通过实例理解深度学习特征，如输入层、隐藏层、输.
Introduction to Neural Networks with TensorFlow
Introduction to Neural Networks with TensorFlow | Udacity
Master the basics of neural networks using Python and TensorFlow, and apply your knowledge to build a functional image classifier. This course guides you through training a deep learning model on an image dataset and deploying it to classify new images.
University: Udacity
Categories: Pyt.
Udacity
Paid Course
3 weeks, 5-6 hours a week
On-Demand