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Deep Learning with Tensor flow

Join and learn distributed techniques such as how parallelism and distribution work using low-level TensorFlow and high-level TensorFlow APIs and Keras.

Intermediate 0(0 Ratings) 0 Students enrolled
Created by Admin mystudyexam Last updated Tue, 28-Jan-2020 English
What will i learn?
  • Learn to process images for machine vision
  • Work with tabular data to make financial predictions
  • Fetch data from an email
  • Predict output probabilities for data
  • Build a RESTful API to make predictions on table data
  • Learn to process text for natural language understanding
  • Generate synthetic test data with machine learning
  • Use encoders to detect sample data
  • Build an automatic email server
  • Create a machine learning model for sentence generation

Curriculum for this course
10 Lessons 01:00:57 Hours
  • Prior working knowledge on Python is assumed
  • Basic knowledge on Math and Statistics is needed
  • Basic knowledge on TensorFlow would be beneficial
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Deep Learning uses a cascade of multiple layers of nonlinear processing units for feature extraction and transformation on large volumes of data in order to make decisions about high dimensional data. 

In this course, You will learn how to design and train your deep learning models and scale them out for larger datasets and complex neural network architectures on multiple GPUs using Google Cloud ML Engine.

Job seekers looking for employment in various IT companies, PSUs or MNCs. Certification in Deep learning with TensorFlow framework benefits Data Science professionals, students and professionals across various Industries.

IT companies, MNCs, Consultancies hire Data Science professionals for Data Science activities. Companies employing Data Science include Capgemini, JP Morgan Chase, TCS, Wipro, Zensar, Accenture, Infor etc.

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  • 01:00:57 Hours On demand videos
  • 10 Lessons
  • Full lifetime access
  • Access on mobile and tv