Artificial Intelligence And Deep Learning Are On The Business School Syllabus

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In a Harvard Business School classroom in Boston, MA, robots are on the rise. MBA students are trying to crack a case study on the self-driving cars pioneered by Tesla, Google, and Uber. What is the potential for robots to reshape our roads? And what are the challenges and opportunities of entering that business? This is a case that David Yoffie, professor of international business administration, believes is essential reading for tomorrow's business leaders.


Deep learning Calculus - Data Science - Machine Learning AI - BuzzTechy

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Udemy Online Course - Deep learning Calculus - Data Science - Machine Learning AI Mastering Calculus for Deep learning / Machine learning / Data Science / Data Analysis / AI using Python You start by learning the definition of function and move your way up for fitting the data to the function which is the core for any Machine learning, Deep Learning, Artificial intelligence, Data Science Application. Once you have mastered the concepts of this course, you will never be blind while applying the algorithm to your data, instead you have the intuition as how each code is working in background. What you'll learn Build Mathematical intuition especially Calculus required for Deep learning, Data Science and Machine Learning The Calculus intuition required to become a Data Scientist / Machine Learning / Deep learning Practitioner How to take their Data Science / Machine Learning / Deep learning career to the next level Hacks, tips & tricks for their Data Science / Machine Learning / Deep learning career Implement Machine Learning / Deep learning Algorithms better Learn core concept to Implement in Machine Learning / Deep learning Who this course is for: Data Scientists who wish to improve their career in Data Science. Deep learning / Machine learning practitioner who wants to take the career to next level Any one who wants to understand the underpinnings of Maths in Data Science, Machine Learning, Deep Learning and Artificial intelligence Any Data Science / Machine Learning / Deep learning enthusiast Any student or professional who wants to start or transition to a career in Data Science / Machine Learning / Deep learning Students who want to refresh and learn important maths concepts required for Machine Learning, Deep Learning & Data Science. Data Scientists who wish to improve their career in Data Science.


Complete Data Science guide -Keras library for deep learning

@machinelearnbot

Keras is an open source neural network library written in Python. It is capable of running on top of MXNet, Deep learning Tensorflow, CNTK, or Theano. Designed to enable fast experimentation with deep neural networks, it focuses on being minimal, modular, and extensible. This course provides a comprehensive expert level details in deep learning(Keras). We start by a brief recap of the most common concepts found in machine learning.


Deep Learning Computer Vision CNN, OpenCV, YOLO, SSD & GANs

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Use Python & Keras to do 24 Projects - Recognition of Emotions, Age, Gender, Object Detection, Segmentation, Face Aging Master Computer Vision using Deep Learning in Python. You'll be learning to use the following Deep Learning frameworks. In this course, you will discover the power of Computer Vision in Python, and obtain skills to dramatically increase your career prospects as a Computer Vision developer.Computer vision applications involving Deep Learning are booming! Having Machines that can'see' will change our world and revolutionize almost every industry out there. Machines or robots that can see will be able to: Perform surgery and accurately analyze and diagnose you from medical scans.


jupyter/jupyter

@machinelearnbot

Recitations from Tel-Aviv University introductory course to computer science, assembled as IPython notebooks by Yoav Ram. Exploratory Computing with Python, a set of 15 Notebooks that cover exploratory computing, data analysis, and visualization. No prior programming knowledge required. Each Notebook includes a number of exercises (with answers) that should take less than 4 hours to complete. Developed by Mark Bakker for undergraduate engineering students at the Delft University of Technology.