Modern Artificial Intelligence with Zero Coding
Build 5 Practical Projects & Harness the Power of AI to solve practical, real-world business problems with Zero Coding!
4.44 (1688 reviews)
14,123
students
9.5 hours
content
Jun 2024
last update
$99.99
regular price
What you will learn
Build, train and deploy AI models to detect people emotions using Google Teachable Machine
Explain the difference between learning rate, epochs, batch size, accuracy and loss.
Predict Insurance Premium using Customer Features such as age, smoking habit and geo-location using AWS AI AutoPilot
Build, train and deploy advanced AI to detect cardiovascular disease using DataRobot AI
Leverage the power of AI to recognize food types using DataRobot AI
Develop an AI model to detect and classify chest disease using X-Ray chest data using Google Teachable Machines
Evaluate trained AI models using various KPIs such as confusion matrix, classification accuracy, and error rate
List the various advantages of transfer learning and know when to properly apply the technique to speed up training process
Understand the theory and intuition behind residual networks, a state-of-the-art deep neural networks that are widely adopted in business, and healthcare
Learn how to train multiple AI models based on XG-Boost, Artificial Neural Networks, Random Forest Classifiers and compare their performance in DataRobot
Understand the impact of classifier threshold on False Positive Rate (Fallout) and True Positive Rate (Sensitivity)
Learn how to use SageMaker Studio AutoML tool to build, train and deploy AI/Ml models which requires almost zero coding experience
Differentiate between various regression models KPIs such as R2 or coefficient of determination, Mean absolute error, Mean Squared error, and Root Mean Squared Error
Build, train and deploy XGBoost-based algorithm to perform regression tasks using AWS SageMaker Autopilot
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3885700
udemy ID
3/2/2021
course created date
3/18/2021
course indexed date
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