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Modern AI Masterclass: Build 6 Real World AI Applications

August 3, 2020 Artificial Intelligence, Udemy CoursesUdemy

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REDEEM

Deal Score+1

REDEEM

Modern AI Masterclass: Build 6 Real World AI Applications

Harness the power of AI to solve practical, real-world problems in Finance, Tech, Art and Healthcare

Created by Dr. Ryan Ahmed, Ph.D., MBA, Kirill Eremenko, Hadelin de Ponteves, SuperDataScience Team, Mitchell Bouchard | 15 hours on-demand video course

Artificial Intelligence (AI) revolution is here!

“Artificial Intelligence market worldwide is projected to grow by US$284.6 Billion driven by a compounded growth of 43. 9%. Deep Learning, one of the segments analyzed and sized in this study, displays the potential to grow at over 42. 5%.” (Source: globenewswire). The purpose of this course is to provide you with knowledge of key aspects of modern Artificial Intelligence applications in a practical, easy and fun way. The course provides students with practical hands-on experience using real-world datasets. The course covers many new topics and applications such as Emotion AI, Explainable AI, Creative AI, and applications of AI in Healthcare, Business, and Finance.

What you’ll learn

• The course provides students with practical hands-on experience using real-world datasets. One key unique feature of this course is that we will be training and deploying models using Tensorflow and AWS SageMaker. In addition, we will cover various elements of the AI/ML workflow covering model building, training, hyper-parameters
• Deploy Emotion AI-based model using Tensorflow 2.0 Serving and use the model to make inference.
• Understand the concept of Explainable AI and uncover the blackbox nature of Artificial Neural Networks and visualize their hidden layers using GradCam technique.
• Develop Deep Learning model to automate and optimize the brain tumor detection processes at a hospital.
• Build and train AI model to detect and localize brain tumors using ResNets and ResUnet networks (Healthcare applications).
• Understand the theory and intuition behind Segmentation models and state of the art ResUnet networks.
• Build, train, deploy AI models in business to predict customer default on credit card using AWS SageMaker XGBoost algorithm.
• Optimize XGBoost model parameters using hyperparameters optimization search.
• Apply AI in business applications by performing customer market segmentation to optimize marketing strategy.
• Understand the underlying theory and mathematics behind DeepDream algorithm for Art generation.
• Develop, train, and test State-of-the art DeepDream algorithm to create AI-based art masterpieces using Keras API in TF 2.0.
• Develop ANNs models and train them in Google’s Colab while leveraging the power of GPUs and TPUs.

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