Artificial Intelligence Course | Learn AI | Artificial Intelligence Tutorial | Intellipaat
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In today's world, Artificial Intelligence (AI) is a very exciting technology that's changing how we live and work. It's like magic computer power that can do things like drive cars by themselves and give us helpful suggestions on our devices. This Artificial Intelligence Course will help you understand What is Artificial Intelligence and how it's changing our lives. So, get ready to learn AI the cool things AI can do and how it's shaping our future!
In this Artificial Intelligence Tutorial, we will learn what is Artificial Intelligence, and How to make a Career in AI. We will start with an introduction to Neural Networks, then What Is Perceptron, Multi-Layer Perceptron, How to Build a Neural Network From Scratch, Activation Functions in ML, and the Best Neural Network Frameworks. Then we will do an introduction to Tensorflow and Keras, Sequential Modelling, CV2 for Image Processing, and Understand network topology and various Parameters for Building Neural Networks. We will learn What Transfer Learning, How to Use VGG and VGG16, Transfer Learning vs. fine Tuning, Problems with CNN, and Understanding RNN & LSTM. Lastly, we will see some Machine Learning Interview Questions that will help you crack any Artificial Intelligence Interview.
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🔵 In this video on Artificial Intelligence Full Course, we will cover the following topics:
What is Artificial Intelligence
How to make a Career in AI?
Introduction to Neural Networks
What Is Perceptron?
Multi-Layer Perceptron
How to Build a Neural Network From Scratch
Building Neural Network with Logistic Regression
Activation Functions in ML
Best Neural Network Frameworks
Introduction to Tensorflow and Keras
Sequential Modelling
CV2 for Image Processing
Understanding network topology and various Parameters for Building Neural Network
How to Train Large Image Models in Batches
TensorBoard for Large Model Performace Monitoring
What Is Transfer Learning?
How to Use VGG and VGG16?
Transfer Learning Vs Fine Tuning
Problems with CNN
Understanding RNN & LSTM
Machine Learning Interview
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