Deep Learning Fundamental Quiz Set is Now Complete
Today I am extremely happy that we have finalise the course work and quizzes to teach Deep Learning Foundations to anyone and everyone.
Now all the teachers, developers and students will study these topic and validate their skill using this quizzes.
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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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Deep Learning with Python Quiz 4
Total Questions: 64
Total Time: 100 minutes
Covers:
Chapter 4 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 machine learning
Four branches of machine learning
Supervised learning
Unsupervised learning
Self-supervised learning
Reinforcement learning
Evaluating machine-learning models
Training, validation, and test sets
Data preprocessing, feature engineering, and feature learning
Data preprocessing for neural networks
Feature engineering
Overfitting and underfitting
Reducing the network's size
Adding weight regularization
Adding dropout
The universal workflow of machine learning
Defining the problem and assembling a dataset
Choosing a measure of success
Deciding on an evaluation protocol
Preparing your data
Developing a model that does better than a baseline
Scaling up: developing a model that overfits
Regularizing your model and tuning your hyperparameters
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Posted by: Zia Khan <ziaukhan@hotmail.com>
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