Welcome ! in this deep learning in python modern advance tutorials for free download, If you want to deep learning so! the free course for you download and watch video learn high level knowledge.
Deep Learning in Python Modern Advance Tutorials For Free
What you will learn in the course:
- Apply momentum to back-propagation to train neural networks
- Understand the basic building blocks of Theano Build network
- Understand the basic building blocks of TensorFlow Build network
- Build a neural network that performs well on the MNIST data-set
- Understand and implement batch normalization in Theano and Tensorflow
Requirements for the course:
- Be comfortable with Python, Numpy, and Matplotlib.
- Install Theano and TensorFlow.
KNOWLEDGE YOU ARE ASSUMED TO HAVE:
- linear algebra
- Python coding: if-else, loops, lists, dicts, sets
- Numpy coding: matrix and vector operations, loading a CSV file
- neural networks and back-propagation
Who is the audience for the course:
- Students and professionals who want to deepen their machine learning knowledge
- Data scientists who want to learn more about deep learning
- Data scientists who already know about back-propagation and gradient descent and want to improve it with stochastic batch training, momentum, and adaptive learning rate procedures like RMSprop
- Those who do not yet know about back-propagation or softmax should take my earlier course, deep learning in Python, first
Course content short overview:
- Outline the MNIST data-set and Linear Logistic Regression Benchmark
- Gradient Descent Full vs Batch vs Stochastic
- Momentum and adaptive learning rates
- Choosing Hyper-parameters
- GPU Speedup, Homework, and Other Misc Topics
- Project Facial Expression Recognition
- Modern Regularization Techniques
deep learning in python modern advance tutorials for free download by clicking below, If you have a any question so! please comment now!
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