Gl Classroom Recordings

Artificial Intelligence with Python

4.49 (99 Ratings)

Intermediate

Skill level

Free

Course cost

This course contains

7.0 Hrs of video content
1 Quiz

Prerequisites

Basics of python, Probability , Calculus

12711 Learners registered

About this course

This comprehensive course on ‘Artificial Intelligence’ covers all the basics of neural network-based models. Get a conceptual understanding of learning mechanisms such as Need and history of neural networks, gradient, forward propagation, loss functions and its implementation using python libraries. Learn some essential concepts related to deep neural networks that also work with Google's powerful library Tensorflow which comes with pre built Keras. We will be covering all theoretical and practical aspects of this subject, in-depth. Dive deeper into the mathematics behind each concept to understand their specifics. We will conclude with a neural network model for classification using MNIST data set. Learn its application on business or real-life problems in other domains.

Skills covered

Perceptron
ANN
Gradient
Backpropagation
Activation Functions
Softmax Function

Course Syllabus

Artificial Intelligence with Python

History behind neural networks
Relationship between biological neuron and artificial neuron
Perceptron and working mechanism
Architecture of artificial neural network
Types of activation functions
Softmax function
Forward propagation
Loss function
Demo using keras framework
Back propagation and gradient descent
Tensorflow 2.0
Demo on MNIST data set

Course Certificate

Get Artificial Intelligence with Python course completion certificate from Great learning which you can share in the Certifications section of your LinkedIn profile, on printed resumes, CVs, or other documents.