Introduction
Unlock the power of AI and machine learning with our comprehensive machine learning training. Delve into the widely utilized statistical analysis technique that spans various industries. This course provides participants with a foundational understanding of neural networks, ensuring a seamless blend of theory and hands-on programming examples. Elevate your expertise, learn, and upskill in machine learning, gaining valuable knowledge to stay ahead. Basic familiarity with linear algebra is recommended for participants diving into the transformative world of AI.
Participants should be familiar with basic linear algebra.
Course Objectives:
- Understand how machine learning is used for prediction
- Grasp the basics of optimization
- Understand how optimization is represented in neural networks
- Apply knowledge to a Python program
Duration
7 hours, 1 Day Course
Mode of Delivery
Classroom-based, Instructor-led Training
Course Outline
- Overview
- What is Machine Learning?
- Applications of Machine Learning in Industry
- Foundational Knowledge
- Vectors and Matrices
- Cost Functions
- Regression
- Multiclass Logistic Regression as Iterated Binary Logistic Regression
- Gradient Descent as Iterated Linear Regression
- The Analogy to Neurons
- Inputs: dendrites
- Outputs: axons
- Parts of a Neural Network
- High-level Representation of a Network
- Input Vector
- Backpropagation
- Activation Functions
- Hidden Layers
- Bias-Variance Trade-off
- Machine Learning in Python
- Tensorflow Constructs
- MNIST
