This course is specially designed for those learners who want to build their career as a TensorFlow developer. The syllabus covered in this course will prepare learners for Google Certificate examination if they wish to take that. We have covered every minute detail and all important topics of TensorFlow along with the appropriate example which will help in solving the programming problems and clearing the doubts. The course is designed in such a way that learner will not feel tough in learning this important framework.

Our Course has more than 10 sections which goes from basic concepts to advance concepts like we start from simple tensor to ragged tensor to more advance concepts like Gradient Tape, or we go from sequential model building to functional model building using this frame work.

Broadly our course is designed keeping the syllabus of Google Certification for TensorFLow in mind which make this course stands apart from other peer courses.

Building a strong Neural Network model whether for classification or for regression is always a promising task and we know that Machine learning rely on this two pillars but their are two big challenges which are always their in building these models the first one is Overfitting and Underfitting, so in this course we will also make you introduce to two important tools Dropout and Callback and how to use them in avoiding overfitting.

Following Topics are broadly covered in our courses

1. Basics of TensorFLow

2. Sequential API

3. Functional API

4. Deep Learning Frame work

5. Convolution Neural Network

6. Basic and Advance Natural Language

7. Lambda Layers

8. Sequence Modelling

9. LSTM

10. Bi-LSTM

11. GRU Cells

12. Customized Neural Network Models