Deep Learning with TensorFlow

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Deep Learning with TensorFlow

TensorFlow concepts, components, pipeline, ANN, Classification, Regression, Object Identification, CNN, RNN, TensorBoard

What you’ll learn

  • End-to-end knowledge of TensorFlow
  • TensorFlow concepts, development, coding, applications
  • TensorFlow components & pipelines
  • TensorFlow examples
  • Introduction to Python, Linear Algebra, Matplotlib, NumPy, Pandas
  • Introduction to Files
  • Introduction to Machine Learning
  • TensorFlow Playground & Perceptrons
  • TensorFlow and Artificial Intelligence
  • Building Artificial Neural Networks (ANN) with TensorFlow
  • Types of ANN and Components of Neural Networks
  • TensorFlow Classification and Linear Regression
  • TensorFlow vs. PyTorch vs. Theano vs. Keras
  • Object Identification in TensorFlow
  • TensorFlow Superkeyword
  • CNN & RNN, RNN Time Series
  • TensorBoard – TensorFlow’s visualization toolkit


  • Enthusiasm and determination to make your mark on the world

Who this course is for:

  • Machine Learning & Deep Learning Engineers
  • Data Scientists & Senior Data Scientists
  • Beginners and newbies aspiring for a career in Machine Learning / Deep Learning
  • Data Analysts & Advanced Data Analytics Professionals
  • TensorFlow Engineers
  • Machine Learning Developers – TensorFlow/Hadoop
  • Software Developers – AI/ML/Deep Learning
  • Anyone wishing to learn TensorFlow algorithms and applications
  • Deep Learning Engineers – Python/TensorFlow
  • Artificial Intelligence Engineers and Senior ML/DL Engineers
  • Researchers and PhD students
  • Data Engineers
  • AI & RPA Developers – TensorFlow/ML
  • AI/ML Developers
  • Machine Learning Leads & Enthusiasts
  • TensorFlow and Advanced ML Developers


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