AI & ML Starter Course with No-Code AI Projects

AI & ML Starter Course with No-Code AI Projects, available at $49.99, has an average rating of 4.09, with 10 lectures, based on 281 reviews, and has 23970 subscribers.

You will learn about Basics of Human Brain & Artificial Neural Network – Biological Neurons & Artificial Neurons Difference between Artificial Intelligence, Machine Learning & Deep Learning 3 Machine Learning Techniques – Supervised Learning, Unsupervised Learning, Reinforcement Learning with examples Learn how to train, evaluate and optimize a Machine Learning model Day in a life of an AI/ML Engineer ML Model Evaluation Method – Confusion Matrix, Error, Recall, Precision, Accuracy ML Model Optimization Method – Learning Rate, Epoch, Batch Size ML Model Training – Using Open-Source Tools Hands-On Project 1 – Build a Machine Learning model using Healthcare Dataset Hands-On Project 2 – Build a Machine Learning model using Agriculture Dataset This course is ideal for individuals who are Those who want to learn the basics of Artificial Intelligence (AI) & Machine Learning (ML) and need hands-on exposure. It is particularly useful for Those who want to learn the basics of Artificial Intelligence (AI) & Machine Learning (ML) and need hands-on exposure.

Enroll now: AI & ML Starter Course with No-Code AI Projects

Summary

Title: AI & ML Starter Course with No-Code AI Projects

Price: $49.99

Average Rating: 4.09

Number of Lectures: 10

Number of Published Lectures: 10

Number of Curriculum Items: 10

Number of Published Curriculum Objects: 10

Original Price: $49.99

Quality Status: approved

Status: Live

What You Will Learn

• Basics of Human Brain & Artificial Neural Network – Biological Neurons & Artificial Neurons
• Difference between Artificial Intelligence, Machine Learning & Deep Learning
• 3 Machine Learning Techniques – Supervised Learning, Unsupervised Learning, Reinforcement Learning with examples
• Learn how to train, evaluate and optimize a Machine Learning model
• Day in a life of an AI/ML Engineer
• ML Model Evaluation Method – Confusion Matrix, Error, Recall, Precision, Accuracy
• ML Model Optimization Method – Learning Rate, Epoch, Batch Size
• ML Model Training – Using Open-Source Tools
• Hands-On Project 1 – Build a Machine Learning model using Healthcare Dataset
• Hands-On Project 2 – Build a Machine Learning model using Agriculture Dataset

Who Should Attend

• Those who want to learn the basics of Artificial Intelligence (AI) & Machine Learning (ML) and need hands-on exposure.

Target Audiences

• Those who want to learn the basics of Artificial Intelligence (AI) & Machine Learning (ML) and need hands-on exposure.