Neural Networks Fundamentals using TensorFlow

We must know that Neural Networks has been in the spotlight for quite some time now and you can now get the detailed explanation about it if you attend the latest training. It is making tremendous breakthroughs in many fields such as image recognition, speech, and natural language processing etc. and the main question that you will come across us that when and when not to apply neural networks. The whole field is like a gold mine and new discoveries are being uncovered each day and in order to be a part of this gold rush, you must get your statistics right and many things in mind before you join the course.

If you are an avid follower of Data science and machine learning then you cannot miss the buzz that is around Deep learning skills and from running competitions to open sourcing projects people are trying to get into and companies are tapping into the limited pool of talent. You can now think of taking up Neural Networks Fundamentals using TensorFlow as Example Training at Octovion through the help of trainers who are real time. Many firms are looking for people who have this combo and the prospects that it offers is also huge and you can now enable it.


Neural Networks Fundamentals using TensorFlow course contents

The Neural Networks Fundamentals TensorFlow course will begin with TensorFlow basics such as creating, initializing, saving, feeding, reading, preloading the data and restoring the variables, infrastructure of TensorFlow and how to visualize and evaluate models, TensorFlow mechanics such as inputs, placeholders, building the graphs, training and evaluating the models, the perception of activation functions, learning algorithms, binary and document classification and limitations of the perceptions, from perception to Support vector machines, introduction to artificial Neural Networks, nonlinear decision boundaries, Feedforward and feedback Neural Networks, multilayer perceptions, minimizing the cost function, forward and back propagation, convolutional Neural Networks and their goals and model architecture plus principles, code organizations and launching plus training the model.

If you are now excited and buoyed up with the prospects that deep learning has to offer and you have not begun your journey yet then you can now understand through the training how an application of neural networks and the use of TensorFlow will help solve a real-life problem. You need to know some basics of neural networks and have familiarity with programming and as the code sometimes will have Python examples the trainers will make sure that they are more focused on the concepts and make sure that they are more language agnostic as possible.

Having a background in physics, mathematics and programming is a pre-requisite for the course and you must have involvement in image processing activities. The course will give you knowledge in neural networks and in machine learning algorithms and deep learning. As the online Neural Networks TensorFlow training will have more focus on the fundamentals and which will help you to choose the right technology and how examples can be made in TensorFLow.