When you learn at Mindmajix, you can always rely on team of experts to provide guidance and support, whenever you need it.
Instructor-Guided Lessons and Activities
Learn key objectives through expert-led lectures, discussions, and exercises.
Hands-on practice on Tools
Practice new skills and dive deeper into the day’s key topics
After Each Session
Q & A Session.
Wrap up the session with clarification on concepts and labs, if needed.
End to End Sample Project/Use-Case Explanation
Deep Learning: A revolution in Artificial Intelligence
Limitations of Machine Learning
Discuss the idea behind Deep Learning
Advantage of Deep Learning over Machine learning
3 Reasons to go Deep
Real-Life use cases of Deep Learning
Scenarios where Deep Learning is applicable
The Math behind Machine Learning: Linear Algebra
The Math Behind Machine Learning: Statistics
Samples vs Population
Review of Machine Learning Algorithms
Underfitting and Overfitting
Defining Neural Networks
The Biological Neuron
Multi-Layer Feed-Forward Networks
Training Neural Networks
Stochastic Gradient Descent
Quasi-Newton Optimization Methods
Generative vs Discriminative Models
Loss Function Notation
Loss Functions for Regression
Loss Functions for Classification
Loss Functions for Reconstruction
Defining Deep Learning
Defining Deep Networks
Common Architectural Principals of Deep Networks
Reinforcement Learning application in Deep Networks
Activation Functions – Sigmoid, Tanh, ReLU
What is TensorFlow?
Use of TensorFlow in Deep Learning
Working of TensorFlow
How to install Tensorflow
HelloWorld with TensorFlow
Running a Machine learning algorithms on TensorFlow
Introduction to CNNs
Architecture of a CNN
Convolution and Pooling layers in a CNN
Understanding and Visualizing a CNN
Transfer Learning and Fine-tuning Convolutional Neural Networks
Introduction to RNN Model
Application use cases of RNN
Training RNNs with Backpropagation
Long Short-Term memory (LSTM)
Recursive Neural Tensor Network Theory
Recurrent Neural Network Model
Restricted Boltzmann Machine
Applications of RBM
Collaborative Filtering with RBM
Introduction to Autoencoders
Deep Belief Network
Mindmajix offers advanced TensorFlow interview questions and answers along with TensorFlow resume samples. Take a free sample practice test before appearing in the certification to improve your chances of scoring high.
Have any queries regarding course curriculum, speak to our course advisorConnect with Advisor
Upon successful completion of the program, you will be awarded a Certificate from Mindmajix for TensorFlow Training.
Successfully complete your course and let the community know about your achievement.
Get your certificate by Mindmajix and have it generated to print with your name.
Don’t just show off your achievement to the community, use it to advance in your career.
Work on real time TensorFlow projects - The primary goal of this project work is to to gear up the skill set required and amplify individual competencies, experience, exposure which align with the current job market to addresses real world business challenges.
Have questions? We’ve got the answers. Get the details on how you can grow in this course.
Our trainers have relevant experience in implementing real-time solutions on different queries related to different topics. Mindmajix verifies their technical background and expertise.
We record each LIVE class session you undergo through and we will share the recordings of each session/class.
Trainer will provide the Environment/Server Access to the students and we ensure practical real-time experience and training by providing all the utilities required for the in-depth understanding of the course.
If you are enrolled in classes and/or have paid fees, but want to cancel the registration for certain reason, it can be attained within 48 hours of initial registration. Please make a note that refunds will be processed within 30 days of prior request.
The Training itself is Real-time Project Oriented.
There are some Group discounts available if the participants are more than 2.
As we are one of the leading providers of Live Instructor LED training, We have customers from USA, UK, Canada, Australia, UAE, Qatar, NZ, Singapore, Malaysia, India and other parts of the world. We are located in USA. Offering Online Training in Cities like
New York, New jersey, Dallas, Seattle, Baltimore, Houston, Minneapolis, Los Angeles, San Francisco, San Jose, San Diego, Washington DC, Chicago, Philadelphia, St. Louis, Edison, Jacksonville, Towson, Salt Lake City, Davidson, Murfreesboro, Atlanta, Alexandria, Sunnyvale, Santa clara, Carlsbad, San Marcos, Franklin, Tacoma, California, Bellevue, Austin, Charlotte, Garland, Raleigh-Cary, Boston, Orlando, Fort Lauderdale, Miami, Gilbert, Tempe, Chandler, Scottsdale, Peoria, Honolulu, Columbus, Raleigh, Nashville, Plano, Toronto, Montreal, Calgary, Edmonton, Saint John, Vancouver, Richmond, Mississauga, Saskatoon, Kingston, Kelowna, Hyderabad, Bangalore, Pune, Mumbai, Delhi, Dubbai, Doha, Melbourne, Brisbane, Perth, Wellington, Auckland etc…
In tensorflow online course, you’ll develop a clear understanding of the motivation for deep learning, and design intelligent systems that learn from complex and/or large-scale datasets. We’ll show you how to train and optimize basic neural networks, convolutional neural networks, and long short term memory networks.
You will learn to solve new classes of problems that were once thought prohibitively challenging, and come to better appreciate the complex nature of human intelligence as you solve these same problems effortlessly using deep learning methods.
Tensorflow is being used by most of the world’s top multinationals. Tensorflow professionals are earning very high salaries when compared with other technologies. With high demand and a number of job opportunities in this field, people who have taken a first course in machine learning, or at least familiar with supervised learning methods will get benefited from this course.
An in-depth knowledge on TensorFlow project which focuses on all the critical components of TensorFlow will be provided by our trainer. As a result, you can increase your visibility and efficiency and draw real connections between different components of TensorFlow. You will also get the complete material covering all the aspects of this project.
The pacing of a course refers to how course teams run the course, and how learners can interact with the course material. Many courses are instructor- paced: they follow a schedule that the instructor sets, with assignments and exams that have specific due dates. In contrast, self-paced courses contain assignments without due dates. You can progress through the course at your own speed.
Instructor-paced courses follow a set schedule. The course team sets specific due dates for assignments and exams, and you complete the course within a defined time period, such as eight or twelve weeks.
Course materials become available at specific times as the course progresses. Assignments have due dates, and exams have start and end dates. In the course outline on the course page, indicators show when you have a graded assignment, as well as the due date for the assignment.
In most instructor-paced courses, certificates are generated within two weeks of the end of the course.
Self-paced courses do not follow a set schedule. Course materials are completely available as soon as the course begins. Assignments and exams do not have start or due dates. The course shows indicators for graded assignments, but not due dates. You can complete assignments and exams at your own pace, as long as you complete all course work before the course ends.
In most self-paced courses, the course team generates certificates on a schedule, such as once a month. The certificate generation schedule varies by course.
Mindmajix guarantees that the educational experience you gain will deliver value even after you complete the course with its course completion certificate. This will undoubtedly be one of the valuable certifications for your career path and your first step in building a career in this course. You can earn this after successful completion of your project work and can get your CV noticed. It also shows you are motivated to learn and that you have genuine expertise.
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