AI for Everyone
2018 will forever be remembered as the year in which AI and Blockchain technologies changed human civilization, the way we lived and did business.
We want to be at the forefront of these disruptive technologies. In this connection we are developing world class curriculum, teachers/developers, projects, and exams to validate our AI and Blockchain knowledge.
The following are three AI quizzes which we have developed so far after putting in a lot of resources, more are also on the way.
Blockchain quizzes have been announced separately.
We will teach these technologies in universities, schools, companies, and on the roads if need be.
Our teacher, developers and students will appear in these tests. You are also invited to do so, if you want to change your life and make Pakistan a software development hub.
Just come to Sir Syed University on any Sunday at 4:00 pm and contact Mr. Inam Ul Haq, the AI Technical Leader.
Pakistan Zindabad
Deep Learning with Python Quiz 1
Total Questions: 35
Total Time: 50 minutes
Covers:
Chapter 1 of Deep Learning with Python by Francois Chollet
https://www.amazon.com/Deep-Learning-Python-Francois-Chollet/dp/1617294438/ref=sr_1_7
FUNDAMENTALS OF DEEP LEARNING
What is deep learning?
Artificial intelligence, machine learning, and deep learning
Learning representations from data
The "deep" in deep learning
What deep learning has achieved so far
Don't believe the short-term hype
The promise of AI
Before deep learning: a brief history of machine learning
Probabilistic modeling
Early neural networks
Kernel methods
Decision trees, random forests, and gradient boosting machines
What makes deep learning different
The modern machine-learning landscape
Why deep learning? Why now?
Hardware, Data, and Algorithms
A new wave of investment
The democratization of deep learning
Will it last?
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Deep Learning with Python Quiz 2
Total Questions: 40
Total Time: 60 minutes
Covers:
Chapter 2 of Deep Learning with Python by Francois Chollet
https://www.amazon.com/Deep-Learning-Python-Francois-Chollet/dp/1617294438/ref=sr_1_7
The mathematical building blocks of neural networks
A first look at a neural network
Data representations for neural networks
Scalars (0D tensors)
Vectors (1D tensors)
Matrices (2D tensors)
3D tensors and higherdimensional tensors
Manipulating tensors in Numpy
The notion of data batches
Real-world examples of data tensors
Vector data
Timeseries data or sequence data
Image data
Video data
The gears of neural networks: tensor operations
Element-wise operations
Broadcasting
Tensor dot
Tensor reshaping
Geometric interpretation of tensor operations
A geometric interpretation of deep learning
The engine of neural networks: gradient-based optimization
What's a derivative?
Derivative of a tensor operation: the gradient
Stochastic gradient descent
Chaining derivatives: the Backpropagation algorithm
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Deep Learning with Python Quiz 3
Total Questions: 45
Total Time: 75 minutes
Covers:
Chapter 3 of Deep Learning with Python by Francois Chollet
https://www.amazon.com/Deep-Learning-Python-Francois-Chollet/dp/1617294438/ref=sr_1_7
One-hot encoding:
https://machinelearningmastery.com/how-to-one-hot-encode-sequence-data-in-python/
Getting started with neural networks
Anatomy of a neural network
Layers: the building blocks of deep learning
Models: networks of layers
Loss functions and optimizers: keys to configuring the learning process
Introduction to Keras
Keras, TensorFlow, Theano, and CNTK
Developing with Keras: a quick overview
Setting up a deep-learning workstation
Classifying movie reviews: a binary classification example
Classifying newswires: a multiclass classification example
Predicting house prices: a regression example
Validating your approach using K-fold validation
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Posted by: Zia Khan <ziaukhan@hotmail.com>
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