Deep Learning using Tensorflow Training
Deep Learning using Tensorflow Course:
TensorFlow, By Google is one of the most popular library for deep learning. Keras is high level library for making deep learning development really easy. At zekelabs, we provide a comprehensive 55 hrs program to master deep learning using tensorflow & keras. scikit-learn is pre-requisite for this course. Staring from scratch to develop production ready code is discussed during live instructor led session. CNN, RNN, Autoencoders, GAN are discussed in details. This is completely hands-on course. Deployment on Cloud, Image classification, Text summerization etc. are integral part of course.
Deep Learning using Tensorflow Course Curriculum
Setting up a deep learning environment
Installing Anaconda and libraries
Intuitively building networks with Keras
Tensorflow Basic Operations-A simple example that cover TensorFlow basic operations.
Tensorflow Logistic Regression-Implement a Logistic Regression with TensorFlow.
Tensorflow K-Means-Build a K-Means classifier with TensorFlow.
Understanding the perceptron
Building a multi-layer neural network
Hidden layers and hidden units
Tuning the loss function
Improving generalization with regularization
Tensorflow Simple Neural Network-MNIST
Getting started with filters and parameter sharing
Optimizing with batch normalization
Experimenting with different types of initialization
Applying a 1D CNN to text
Tensorflow Convolutional Neural Network (tf.layers/estimator api)-MNIST
Implementing a simple RNN
Using gated recurrent units (GRUs)
Character-level text generation
Tensorflow Bi-directional Recurrent Neural Network (LSTM)-MNIST
Auto-Encoder
Understanding GANs
Upscaling the resolution of images with Super Resolution GANs (SRGANs)
Tensorflow DCGAN (Deep Convolutional Generative Adversarial Networks)
Augmenting images with computer vision techniques
Localizing an object in images
Scene understanding (semantic segmentation)
Recognizing faces
Analyzing sentiment
Summarizing text
Visualizing training with TensorBoard and Keras
Using grid search for parameter tuning
Comparing optimizers
Adding dropouts to prevent overfitting
Visualizing training with TensorBoard
Freezing layers
Large-scale visual recognition with GoogLeNet/Inception
Leveraging pretrained VGG models for new classes
CIFAR 10 image classification
Frequently Asked Questions
This "Deep Learning using Tensorflow" 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 Tensorflow"-specific study material. Participants will have lifetime access to all the code and resources needed for this "Deep Learning using Tensorflow". 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 Tensorflow" training.
The "Deep Learning using Tensorflow" 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 Tensorflow" course duration.
The "Deep Learning using Tensorflow" training is organised at the client's premises. We have delivered and continue to deliver "Deep Learning using Tensorflow" 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 Tensorflow" course.
Recommended Courses
|
Deep Learning using Tensorflow |
|
Machine-Learning with Python using scikit-learn & tensorflow |
|
Artificial Intelligence |
|
Apache Kafka |
More Courses
|
Amazon Redshift |
|
Amazon Redshift |
|
Oracle SQL |
|
MongoDB |
|
H2O - Machine Learning |
|
SAP HANA |
|
React |
|
React Native |
|
Ansible |
Read More
Recommended Courses
Machine Learning using AWS SageMaker
Deep Learning using Tensorflow
Machine-Learning with Python using scikit-learn & tensorflow
Feedback