Dive into Deep Learning with Scala

Overview

Delve into the world of deep learning with Scala, a powerful language for data processing and AI applications. This course offers an in-depth exploration of deep learning basics, emphasizing practical implementation using Scala.

Learn about neural networks and computer vision techniques, and access a range of hands-on examples to cement your understanding of these concepts.

Compare various libraries and tools available in Scala to enhance your skill set in deep learning. Whether you're interested in theoretical principles or practical applications, this course provides valuable insights tailored for budding AI enthusiasts and seasoned developers alike.

Presented by experienced professionals on YouTube, this event is a part of a comprehensive series on Artificial Intelligence Courses and Conference Talks, making it an invaluable resource for anyone looking to advance their career in AI and machine learning.

Syllabus

• Introduction to Deep Learning
Overview of Artificial Intelligence and Machine Learning
Evolution and significance of Deep Learning
Role of Scala in Deep Learning
• Basics of Neural Networks
Anatomy of a Neural Network
Activation Functions
Loss Functions and Optimization Algorithms
• Setting Up the Scala Environment
Installation and configuration of Scala
Overview of popular Scala libraries for Deep Learning (Breeze, DeepLearning.scala, Spark MLlib)
• Core Deep Learning Concepts
Multilayer Perceptrons
Backpropagation and Gradient Descent
Regularization Techniques
• Convolutional Neural Networks (CNNs)
Architecture and components of CNNs
CNNs for Image Classification and Object Detection
Practical implementation of CNNs in Scala
• Recurrent Neural Networks (RNNs)
Fundamentals of RNNs and LSTMs
Applications of RNNs in Time Series and NLP
Building RNN models with Scala
• Deep Learning Model Evaluation
Metrics for assessing model performance
Validation and Testing Strategies
Hyperparameter Tuning
• Practical Applications and Case Studies
Case Study: Implementing a Computer Vision task with Scala
Hands-on example: Building a Sentiment Analysis model
Comparison of Deep Learning Libraries in Scala
• Advanced Topics
Transfer Learning and Pretrained Models
Generative Adversarial Networks (GANs)
Ethical considerations in AI and Deep Learning
• Capstone Project
Develop and present a deep learning project using Scala
Peer review and feedback session
• Course Conclusion
Summary of key concepts
Future learning paths in Deep Learning and Scala

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Subjects

Conference Talks