All current Long short-term memory (LSTM) Courses courses in 2024
17 Courses
Deep Learning Bootcamp with 5 Capstone Projects
Deep Learning Bootcamp with 5 Capstone Projects
Enroll in our intensive Deep Learning Bootcamp to gain comprehensive knowledge in artificial neural networks (ANN), convolutional neural networks (CNN), recurrent neural networks (RNN), and long short-term memory (LSTMs). This course offers hands-on experience through five real-time capstone projec.
Practical Deep Learning with Python
Welcome to the Practical Deep Learning with Python course, a comprehensive program designed to provide hands-on experience with advanced deep learning techniques. Leverage the power of AI to model and analyze complex datasets, offering real-world solutions and insights from large data volumes.
This curriculum focuses on practical skills essen.
Deep Learning
Artificial neural networks form the foundation of modern AI systems. “Deep Learning” offers participants a comprehensive introduction to the core principles and fundamental building blocks used in today’s neural networks. The course covers the most important types of neural networks, like MLPs, CNNs, RNNs, and Transformers, as well as practical.
PyTorch for Deep Learning Bootcamp: Zero to Mastery
Elevate your understanding of Deep Learning with the PyTorch for Deep Learning Bootcamp: Zero to Mastery. Offered by Udemy, this comprehensive course is designed for individuals eager to dive into the world of Machine Learning using the powerful PyTorch library developed by Facebook. Gain hands-on experience with practical examples that cover.
Artificial Intelligence III - Deep Learning in Java
Embark on an in-depth journey into the world of Artificial Intelligence with the "Artificial Intelligence III - Deep Learning in Java" course by Udemy. Dive into core concepts of deep learning, including Deep Learning Fundamentals, Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs) along with advanced topics like LSTM.
深度学习
本课程主要面向计科、人工智能及物联网专业的本科生，讲述深度学习基本概念、经典深度学习模型及其实践，主要内容包括前馈神经网络、深度模型优化与正则化、卷积神经网络、循环神经网络等，并介绍深度学习框架的编码实现和参数优化方法。本课程注重理论学习与实践应用的结合，除了课堂讲授之外，还将通过实践环节引导学生使用深度学习平台或工具，让学生通过实际应用来加深.
Advanced RNN Concepts and Projects
Advanced RNN Concepts and Projects
This advanced course on Recurrent Neural Networks (RNNs) addresses key challenges like the vanishing gradient problem and provides solutions such as Gated Recurrent Units (GRUs) and Long Short Term Memory (LSTM) networks. You'll start with an overview of improved RNN modules and delve into bidirectional RNNs a.
RNNs and Transformers
RNNs and Transformers - Udacity
Explore the intricacies of RNN architectures and their design patterns in this comprehensive course offered by Udacity. Additionally, gain a deep understanding of transformer architectures and how they differ from traditional RNN models. Perfect for those interested in deep learning, sentiment analysis, and advanc.
Udacity
Paid Course
4 weeks
On-Demand
Fundamentals of CNNs and RNNs
Fundamentals of CNNs and RNNs
This course covers fundamental concepts of convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which are widely used in computer vision and natural language processing areas.
In the CNN part, you will learn the concepts of CNNs, the two major operators (convolution and pooling), and t.
Coursera
Free Online Course (Audit)
5-6 hours
On-Demand
Stanford Seminar - Transformers in Language: The Development of GPT Models Including GPT-3
Title: Stanford Seminar on GPT Models: Unveiling Transformers in Language
Description: Dive into the world of unsupervised learning and its pivotal role in natural language processing with our comprehensive Stanford University course, available on YouTube. Explore an array of algorithms pivotal for constructing generative text models and enhancing.
YouTube
Free Online Course
49 minutes
On-Demand