Deep Learning using Python-training-in-bangalore-by-zekelabs

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-training-in-bangalore-by-zekelabs
Deep Learning using Python-training-in-bangalore-by-zekelabs
Industry Level Projects
Deep Learning using Python-training-in-bangalore-by-zekelabs

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
Speech production
What is deep learning?
Feature learning
Deep learning applications
Object recognition and classification
Popular open source libraries – an introduction
Sample deep neural net code using Keras
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
Recurrent neural networks
Backpropagation through time
Long short term memory
Word-based models
Neural language models
Preprocessing and reading data
Example training
Speech recognition pipeline
Deep belief networks
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 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
Electrocardiogram pulse detection
What is a data product?
Weights initialization
Adaptive learning
Newton's method
Sparkling Water
Model validation
Unlabeled Data
Hyper-parameters tuning
A/B Testing
Anomaly score APIs

Frequently Asked Questions

We have options for classroom-based as well as instructor led live online training. The online training is live and the instructors screen will be visible and voice will be audible. Your screen will also be visible and you can ask queries during the live session.

The training on "Deep Learning using Python" course is a hands-on training. All the code and exercises will be done in the live sessions. Our batch sizes are generally small so that personalized attention can be given to each and every learner.

We will provide course-specific study material as the course progresses. You will have lifetime access to all the code and basic settings needed for this "Deep Learning using Python" through our GitHub account and the study material that we share with you. You can use that for quick reference

Feel free to drop a mail to us at [email protected] and we will get back to you at the earliest for your queries on "Deep Learning using Python" course.

We have tie-ups with a number of hiring partners and and placement assistance companies to whom we connect our learners. Each "Deep Learning using Python" course ends with career consulting and guidance on interview preparation.

Minimum 2-3 projects of industry standards on "Deep Learning using Python" will be provided.

Yes, we provide course completion certificate to all students. Each "Deep Learning using Python" training ends with training and project completion certificate.

You can pay by card (debit/credit), cash, cheque and net-banking. You can also pay in easy installments. You can reach out to us for more information.

We take pride in providing post-training career consulting for "Deep Learning using Python".

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