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Deep Learning Essentials Bootcamp
Description
Deep Learning Essentials Bootcamp Introduction
Welcome to the Deep Learning Essentials Bootcamp, a comprehensive two-day event designed to immerse you in the innovative field of deep learning. As a pivotal branch of artificial intelligence, deep learning mimics human intelligence using complex neural networks. Our program is tailored to equip you with the expertise to navigate and master this cutting-edge technology.
Throughout the bootcamp, you will engage with the core principles and methodologies of deep learning, utilizing popular frameworks such as TensorFlow and Keras. The curriculum is structured to balance theoretical knowledge with extensive hands-on practice, comprising 40% lab sessions. These practical sessions will enhance your ability to construct, train, and optimize neural networks, preparing you to implement these models effectively with tools like TensorFlow Serving.
By the conclusion of this immersive experience, you will not only understand the intricate details of deep learning but will also be proficient in applying Python to develop and fine-tune models. This course is your gateway to advancing your skills in data science and preparing for real-world data challenges under the mentorship of industry experts.
Deep Learning Essentials Bootcamp Course Objectives
- Master Deep Learning Fundamentals: Understand the core principles, theories, and mathematical foundations of deep learning.
- Tool Proficiency: Become adept with Anaconda and Jupyter Notebook, essential tools for every data scientist.
- Comprehensive Framework Usage: Develop skills in building, training, and deploying neural networks using Python, TensorFlow, and Keras.
- Python and Libraries: Dive deep into Python and its powerful libraries, enhancing your proficiency in TensorFlow and Keras for deep learning applications.
- Data Preprocessing Skills: Acquire critical techniques in data preprocessing to prepare datasets effectively for machine learning models.
- Model Optimization: Learn to fine-tune and optimize your deep learning models for peak performance, understanding the application of various optimizers.
- Bonus Content: Explore the functionalities of GPT and Generative AI in deep learning, applying these advanced technologies to real-world scenarios.
Prerequisites
To ensure a smooth learning experience and maximize the benefits of attending this course, you should have the following prerequisite skills:
- Python programming is required, as the labs revolve around leveraging Python. Basic skills in handling and manipulating data using Python libraries such as NumPy and Pandas would be advantageous.
- Familiarity with concepts such as variables, functions, control flow, and data structures will ensure a smooth learning experience.
- While the course will introduce deep learning from scratch, having a grasp of basic machine learning concepts will be beneficial.
- Some understanding of algebra and basic calculus will be helpful in comprehending the mathematical components of deep learning.
Audience
- This intermediate and beyond level course is geared for experienced professionals aiming to apply machine learning and deep learning to solve complex business problems, including product managers, data analysts, data scientists, developers, team leads, and other technical stakeholders who want to leverage deep learning for strategic decisions.
- It’s also suited for those who are in roles that require them to work with data, understand patterns, or make predictions, such as business analysts, software developers, and researchers.
- Python experience is required.
Deep Learning Essentials Bootcamp Outline
Introduction to Deep Learning
- Understand the concept and significance of deep learning in modern business.
- Fundamental concepts in deep learning like neurons, layers, weights, bias, and activation functions.
- Real-world use cases of deep learning in business.
Setting up Deep Learning Environment
- Understand how to create an effective deep learning environment.
- Basics of Anaconda and Jupyter notebook.
- Lab: Set up a Python environment
Introduction to TensorFlow and Keras
- Get an overview of TensorFlow and Keras.
- Learn the process of creating a simple neural network using Keras.
- Lab: Build a basic neural network
Fundamentals of Neural Networks
- Understand what neural networks are and how they function.
- Learn about forward propagation and backpropagation in a neural network.
- Lab: Implement a Multi-Layer Perceptron (MLP) on a simple dataset
Working with Data in Deep Learning
- Understand the importance of data preprocessing in deep learning.
- Learn how to handle and preprocess different types of data – images, text, etc.
- Lab: Preprocess a dataset for a deep learning task
Tuning and Optimizing Deep Learning Models
- Learn about different types of optimizers – SGD, Adam, RMSprop, etc.
- Learn how to save and load trained models.
- Lab: Tune and optimize a neural network model
Deploying Deep Learning Models
- Understand how to deploy deep learning models.
- Learn about serving models with TensorFlow Serving.
- Lab: Deploy a trained model
Real-world Applications of Deep Learning
- Understand the real-world applications of deep learning.
- Overview of deep learning in healthcare, finance, transportation, and more.
$1995.00
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2 Days Course |