Deep Learning using Python Training
Deep Learning using Python Course:
Keras is a high-level neural networks API, written in Python and capable of running on top of either TensorFlow, CNTK or Theano. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result with the least possible delay is key to doing good research. In this course, we extensively cover deep learning using Keras
Deep Learning using Python Course Curriculum
What is machine learning?
Supervised learning
Reinforcement learning
Brief description of popular techniques/algorithms
Decision trees
Naïve Bayes
The cross-entropy method
Deep learning
Why neural networks?
Neurons and layers
The back-propagation algorithm
Logistic regression
Applications in industry
Medical
Business
Speech production
What is deep learning?
Feature learning
Deep learning applications
Object recognition and classification
Popular open source libraries – an introduction
TensorFlow
Sample deep neural net code using Keras
Autoencoders
Regularization techniques for autoencoders
Contractive autoencoders
Summary of autoencoders
Hopfield networks and Boltzmann machines
Restricted Boltzmann machine
Deep belief networks
Similarities between artificial and biological models
Convolutional layers
Pooling layers
Convolutional layers in deep learning
A convolutional layer example with Keras to recognize digits
Pre-training
Recurrent neural networks
Backpropagation through time
Long short term memory
Word-based models
Neural language models
Preprocessing and reading data
Training
Example training
Speech recognition pipeline
Preprocessing
Deep belief networks
CTC
Decoding
Early game playing AI
Implementing a Python Tic-Tac-Toe game
Training AI to master Go
Deep learning in Monte Carlo Tree Search
Policy gradients for learning policy functions
A supervised learning approach to games
Q-Learning
Q-learning in action
Experience replay
Atari Breakout
Preprocessing the screen
Convergence issues in Q-learning
Actor-critic methods
Generalized advantage estimator
Model-based approaches
What is anomaly and outlier detection?
Popular shallow machine learning techniques
Detection modeling
H2O
Examples
Electrocardiogram pulse detection
What is a data product?
Weights initialization
Adaptive learning
Momentum
Newton's method
Adadelta
Sparkling Water
Model validation
Unlabeled Data
Hyper-parameters tuning
A/B Testing
Deployment
Anomaly score APIs
Frequently Asked Questions
This "Deep Learning using Python" course is an instructor-led training (ILT). The trainer travels to your office location and delivers the training within your office premises. If you need training space for the training we can provide a fully-equipped lab with all the required facilities. The online instructor-led training is also available if required. Online training is live and the instructor's screen will be visible and voice will be audible. Participants screen will also be visible and participants can ask queries during the live session.
Participants will be provided "Deep Learning using Python"-specific study material. Participants will have lifetime access to all the code and resources needed for this "Deep Learning using Python". Our public GitHub repository and the study material will also be shared with the participants.
All the courses from zekeLabs are hands-on courses. The code/document used in the class will be provided to the participants. Cloud-lab and Virtual Machines are provided to every participant during the "Deep Learning using Python" training.
The "Deep Learning using Python" training varies several factors. Including the prior knowledge of the team on the subject, the objective of the team learning from the program, customization in the course is needed among others. Contact us to know more about "Deep Learning using Python" course duration.
The "Deep Learning using Python" training is organised at the client's premises. We have delivered and continue to deliver "Deep Learning using Python" training in India, USA, Singapore, Hong Kong, and Indonesia. We also have state-of-art training facilities based on client requirement.
Our Subject matter experts (SMEs) have more than ten years of industry experience. This ensures that the learning program is a 360-degree holistic knowledge and learning experience. The course program has been designed in close collaboration with the experts working in esteemed organizations such as Google, Microsoft, Amazon, and similar others.
Yes, absolutely. For every training, we conduct a technical call with our Subject Matter Expert (SME) and the technical lead of the team that undergoes training. The course is tailored based on the current expertise of the participants, objectives of the team undergoing the training program and short term and long term objectives of the organisation.
Drop a mail to us at [email protected] or call us at +91 8041690175 and we will get back to you at the earliest for your queries on "Deep Learning using Python" course.
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