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