Available Training Rooms

  • PRIVATE BATCH
  • PUBLIC PROGRAM
  • ON DEMAND
  • BLENDED

Course Details

• What is machine learning, and what kinds of problems can it solve?
• What are the five phases of converting a candidate use case to be driven by machine learning, and why is it important that the phases not be skipped?
• Why are neural networks so popular now?
• How can you set up a supervised learning problem and find a good, generalizable solution using gradient descent and a thoughtful way of creating datasets?
• Learn how to write distributed machine learning models that scale in Tensorflow 2.x, scale out the training of those models. and offer high-performance predictions.
• Convert raw data to features in a way that allows ML to learn important characteristics from the data and bring human insight to bear on the problem.
• Finally, learn how to incorporate the right mix of parameters that yields accurate, generalized models and knowledge of the theory to solve specific types of ML problems.
• You will experiment with end-to-end ML, starting from building an ML-focused strategy and progressing into model training, optimization, and productionalization with hands-on labs using Google Cloud.

Audience

  • Data Scientist
  • Data Analyst

Public Program Schedule

There is no upcoming Public Batch Schedule, you can ask for Private Batch or for On-Demand Learning
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The highest standard, The happiest learners

Anirban Chatterjee
Manager (Global Projects & Pilot Desk) | HSBC Operations

Special thanks to you for suggesting such a brilliant trainer Raja Gopalan for DevOps. It was a well tailored course as per our requirement. We all simply enjoyed the sessions and definitely looking forward towards a long term engagement.

Ikram
Veritas

Really appreciate your efforts behind making this training a big success, especially considering the diverse levels of participant expertise on the subject. The participants have provided great feedback around the training

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