Artificial Neural Networks ANN With Keras in Python And R

Artificial Neural Networks ANN With Keras in Python And R – Are you trying to find an entire Course on Deep Learning using Keras and Tensorflow that teaches you everything you would like to make a Neural Network model in Python and R, right?

Artificial Neural Networks ANN With Keras in Python And R - Artificial Neural Networks, ANN, AI, AI models, Artificial Intelligence, Deep NeuroEvolution, Data Science, Machine Learning, Keras, Python, R Language, Advanced algorithms, Deep Learning, Matplotlib stack, Neural Networks, neural style, NumPy, Numpy Stack, Tensorflow

After completing this course you will be able to:

  • Identify the business problem that can be solved by using Neural Network Models.
  • Comprehensive understanding of Advanced Neural network concepts such as Gradient Descent, forward and Backward Propagation etc.
  • Create Modem Neural network models in Python and R using Keras and Tensorflow libraries to analyze results.
  • Confidently practice, discuss and understand Artificial Neural Networks Deep Learning concepts

Also Read: Python Programming Beginners Tutorial Full Course
Read: Python Programming For Beginners Data Science Full Course
Also Read: Complete Beginners Introduction To Web Development

Description

A Globally Verifiable Certificate of Completion is awarded to all students who undertake this Neural networks course. If you are starting career in business Analyst or an executive, or a student who wants to learn, understand and apply Deep learning in Real world problems of business, this perfect course will give you a solid base for that by teaching  some most advanced concepts of Neural networks and their Realtime implementation in Python without getting too Mathematical.

Why should you choose this course?

This course covers all aspects that someone should take to create a predictive model using Neural Networks from scratch. Many training courses focus only on teaching how to run the analysis but we strongly believe that having a strong theoretical understanding of the concepts enables some to create a good model . And after running the analysis, one should be able to understand how good the model is and interpret the results to help the business.

Who this course is for:

  • People or students pursuing a career in data science
  • Anyone curious to master ANN from Beginner level in very short span of time

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