ARTIFICIAL INTELLIGENCE COMPLETE COURSE
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Artificial Intelligence Complete Course helps you master the essentials of text processing and classifying texts along with important concepts such as Tokenization, Stemming, Lemmatization, POS tagging, and many more. You will learn to perform image pre-processing, image classification, transfer learning, object detection, and computer vision and also be able implement popular algorithms like CNN, RCNN, RNN, LSTM, RBM using the latest TensorFlow 2.0 package in Python. This course is curated by the industry experts after an extensive research to meet the latest industry requirements and demands. Unleash the power of Artificial Intelligence and accelerate your career— join the global revolution now!
WHAT YOU WILL LEARN
WHAT YOU WILL LEARN
Build 7 different AIs for 7 different applications
Understand the theory behind Artificial Intelligence
Master the State of the Art AI models
Solve Real World Problems with AI
Q-Learning
Deep Q-Learning
Deep Convolutional Q-Learning
A3C (Asynchronous Advantage Actor-Critic)
PPO (Proximal Policy Optimization)
SAC (Soft Actor-Critic)
LLMs
Transformers
Low-Rank Adaptation (LoRA) and Quantization (QLoRA)
NLP techniques for Chatbots: Tokenization and Padding
Fine-Tuning an LLM with Knowledge Augmentation
As Extras: DDPG, Full World Model, Evolution Strategies & Genetic Algorithms
COURSE CONTENT
COURSE CONTENT
Part 0 - Fundamentals of Reinforcement Learning
Welcome to Part 0 - Fundamentals of Reinforcement Learning
Q-learning Intuition
Q-learning Intuition
Plan of Attack
What is reinforcement learning ?
The Bellman Equation
The "Plan"
Markov Decision Process
Policy vs Plan
Adding a "Living Penalty"
Preview
Q-Learning Intuition
Temporal Difference
Q-Learning Implementation
Q-Learning Implementation
A Q-Learning Implementation for Process Optimization
Part 1-Deep Q-Learning
Part 1-Deep Q-Learning
Welcome to Part 1 - Deep Q-Learning
Deep Q-Learning Intuition
Deep Q-Learning Intuition
Plan of Attack
Deep Q-Learning Intuition - Learning
Deep Q-Learning Intuition - Acting
Experience Replay
Action Selection Policies
Deep Q-Learning Implementation
Deep Q-Learning Implementation
Get the Codes here
Deep Q-Learning Implementation - Step 1
Deep Q-Learning Implementation - Step 2
Deep Q-Learning Implementation - Step 3
Deep Q-Learning Implementation - Step 4
Deep Q-Learning Implementation - Step 5
Deep Q-Learning Implementation - Step 6
Deep Q-Learning Implementation - Step 7
Deep Q-Learning Implementation - Step 8
Deep Q-Learning Implementation - Step 9
Deep Q-Learning Implementation - Step 10
Deep Q-Learning Implementation - Step 11
Deep Q-Learning Implementation - Step 12
Deep Q-Learning Implementation - Step 13
Deep Q-Learning Implementation - Step 14
Deep Q-Learning Implementation - Step 15
Deep Q-Learning Implementation - Step 16
Deep Q-Learning Implementation - Step 17
Deep Q-Learning Implementation - Step 18
Deep Q-Learning Implementation - Step 19
Deep Q-Learning Implementation - Step 20
Part 2- Deep Convolutional Q-Learning
Part 2- Deep Convolutional Q-Learning
Welcome to Part 2 - Deep Convolutional Q-Learning
Deep Convolutional Q-Learning Intution
Deep Convolutional Q-Learning Intution
Plan of Attack
Deep Convolutional Q-Learning Intuition
Eligibility Trace
Deep Convolutional Q-Learning Implementation
Deep Convolutional Q-Learning Implementation
Get the Codes here
Deep Convolutional Q-Learning Implementation - Step 1
Deep Convolutional Q-Learning Implementation - Step 2
Deep Convolutional Q-Learning Implementation - Step 3
Deep Convolutional Q-Learning Implementation - Step 4
Deep Convolutional Q-Learning Implementation - Step 5
Deep Convolutional Q-Learning Implementation - Step 6
Deep Convolutional Q-Learning Implementation - Step 7
Deep Convolutional Q-Learning Implementation - Step 8
Deep Convolutional Q-Learning Implementation - Step 9
Deep Convolutional Q-Learning Implementation - Step 10
Deep Convolutional Q-Learning Implementation - Step 11
Deep Convolutional Q-Learning Implementation - Step 12
Deep Convolutional Q-Learning Implementation - Step 13
Part 3-A3C
Welcome to Part 3 - A3C
A3C Intution
A3C Intution
Plan of Attack
The three A's in A3C
Actor-Critic
Asynchronous
Advantage
LSTM Layer
A3C Implementation
A3C Implementation
Get the Codes here
A3C Implementation - Step 1
A3C Implementation - Step 2
A3C Implementation - Step 3
A3C Implementation - Step 4
A3C Implementation - Step 5
A3C Implementation - Step 6
A3C Implementation - Step 7
A3C Implementation - Step 8
A3C Implementation - Step 9
A3C Implementation - Step 10
A3C Implementation - Step 11
A3C Implementation - Step 12
A3C Implementation - Step 13
A3C Implementation - Step 14
A3C Implementation - Step 15
Part 4-PPO and SAC
Part 4-PPO and SAC
Build and Train the PPO and SAC models for a Self-Driving Car! Theory included.
Part 5-Intro to large language models(LLMs)
Part 5-Intro to large language models(LLMs)
Welcome to Part 5 - Intro to Large Language Models (LLMs)
LLMs Intution
LLMs Intution
Introduction to LLMs
Ingredients of an LLM
Who invented LLMs?
How LLMs generate text
Inside an LLM - Under the Hood
LLM Parameters
LLM Context Window
Fine-Tuning LLMs
LLMs Implementation
LLMs Implementation
Get the Codes here
Fine-Tuning LLMs with Hugging Face - Step 1
Fine-Tuning LLMs with Hugging Face - Step 2
Fine-Tuning LLMs with Hugging Face - Step 3
Fine-Tuning LLMs with Hugging Face - Step 4
Fine-Tuning LLMs with Hugging Face - Step 5
Fine-Tuning LLMs with Hugging Face - Step 6
Fine-Tuning LLMs with Hugging Face - Step 7
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