DEEP LEARNING FOUNDATION
Course 3317
3 Days
$1,800
Dive into the core concepts of deep learning and discover how to build powerful models that can solve complex problems. This course will provide you with the essential knowledge and hands-on experience to start creating your own deep learning projects.
Who Should Take This Course?
This course is perfect for data scientists, machine learning enthusiasts, engineers, and anyone interested in mastering the basics of deep learning.
Course Format:
Lectures, facilitator presentations, guided discussions, practical hands-on exercises (both individual and large-group), collaborative discussions, and action planning.
Payment Information: We accept credit card payments. To register using a purchase order (without a surcharge), please send the purchase order to [email protected]
Learning Objectives
- Understand the fundamental concepts and architectures of deep learning.
- Build and train neural networks using popular deep learning frameworks.
- Implement key techniques such as backpropagation and gradient descent.
- Apply convolutional neural networks (CNNs) to image-related tasks.
- Use recurrent neural networks (RNNs) for sequence data analysis.
- Evaluate and optimize deep learning models for better performance.
Course Topics
Introduction to Deep Learning
- Overview of NLP and its importance in business
- Differences between deep learning and traditional machine learning
Neural Networks Basics
- Understanding neurons, layers, and activation functions
- Building your first neural network
Sentiment Analysis
- Understanding sentiment analysis and its applications
- Tools and techniques for sentiment detection
Text Classification and Topic Modeling
- Categorizing text data into relevant topics
- Applying topic modeling to uncover hidden themes
Training Neural Networks
- Concepts of backpropagation and gradient descent
- Techniques for training and optimizing neural networks
Convolutional Neural Networks (CNNs)
- Introduction to CNNs and their applications in image processing
- Building and training CNN models
Recurrent Neural Networks (RNNs)
- Understanding RNNs and their use in sequence data
- Implementing RNNs for tasks like language modeling and time series prediction
Deep Learning Frameworks
- Overview of popular frameworks such as TensorFlow and PyTorch
- Hands-on exercises with selected frameworks
Prerequisites
To make the most out of this course, you should have:
Class Schedule
We accept credit card payments. To register using a purchase order (without a surcharge), please send the purchase order to [email protected]
August 14 - August 16, 2024
9:00 AM – 5:00 PM EST
Deep Learning Foundation
Virtual, EST
$1,100
Class ID: 3317
September 11 - September 13, 2024
9:00 AM – 5:00 PM EST
Deep Learning Foundation
Virtual, EST
$1,100
Class ID: 3317
October 16 - October 18, 2024
9:00 AM – 5:00 PM EST
Deep Learning Foundation
Virtual, EST
$1,100
Class ID: 3317
November 13 - November 15, 2024
9:00 AM – 5:00 PM EST
Deep Learning Foundation
Virtual, EST
$1,100
Class ID: 3317
January 14 - January 16, 2025
9:00 AM – 5:00 PM EST
Deep Learning Foundation
Virtual, EST
$1,100
Class ID: 3317
February 11 - February 13, 2025
9:00 AM – 5:00 PM EST
Deep Learning Foundation
Virtual, EST
$1,100
Class ID: 3317
March 18 - March 20, 2025
9:00 AM – 5:00 PM EST
Deep Learning Foundation
Virtual, EST
$1,100
Class ID: 3317