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Deep learning Online Training

http://www.learntek.org/product/deep-learning-training/ Learntek is global online training provider on Big Data Analytics, Hadoop, Machine Learning, Deep Learning, IOT, AI, Cloud Technology, DEVOPS, Digital Marketing and other IT and Management courses. We are dedicated to designing, developing and implementing training programs for students, corporate employees and business professional. www.learntek.org

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Deep learning Online Training

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  1. DEEP LEARNING

  2. The following topics will be covered in our Deep Learning  Online Training: Copyright @ 2015 Learntek. All Rights Reserved.

  3. Deep Learning with TensorFlow • Deep Learning is a subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks. It is intersection of statistics, artificial intelligence, and data to build accurate models. TensorFlow is one of the newest and most comprehensive libraries for implementing deep learning. With deep learning going mainstream, making sense of data and getting accurate results using deep networks is possible. Copyright @ 2015 Learntek. All Rights Reserved.

  4. How it works • A deep learning model is designed to continually analyze data with a logic structure like how a human would draw conclusions. To achieve this, deep learning uses a layered structure of algorithms called an artificial neural network (ANN). Copyright @ 2015 Learntek. All Rights Reserved.

  5. What you will learn from this course • This course will offer you an opportunity to explore various complex algorithms for deep learning. You will also learn how to train model to derive new features to make sense of deeper layers of data. Using TensorFlow, you will learn how to train model in supervise and unsupervised category. Copyright @ 2015 Learntek. All Rights Reserved.

  6. Introduction to Deep learning • AI and Deep learning • Advantage of Deep learning • Deep Learning Primitives • Deep Learning Architecture • The Neural viewpoint • The Representation Viewpoint Copyright @ 2015 Learntek. All Rights Reserved.

  7. TensorFlow Fundamentals Copyright @ 2015 Learntek. All Rights Reserved.

  8. Introduction to Neural Network Copyright @ 2015 Learntek. All Rights Reserved.

  9. Linear and Logistic Regression with TensorFlow • Overview of Linear and Logistic Regression • Loss Functions • Gradient Descent • Automatic Differentiation Systems • Learning with TensorFlow • Training Linear and Logistic Regression model • Evaluating Model Accuracy Copyright @ 2015 Learntek. All Rights Reserved.

  10. Convolutional Neural Networks • Visual Cortex Architecture • Convolutional Layer • Filters • Stacking Multiple Feature Maps • TensorFlow Implementation • Pooling/Subsampling • Fully Connected Layer • MNIST digit classification example Copyright @ 2015 Learntek. All Rights Reserved.

  11. Recurrent Neural Networks Copyright @ 2015 Learntek. All Rights Reserved.

  12. Reinforcement Learning Copyright @ 2015 Learntek. All Rights Reserved.

  13. Prerequisites : • Basic understanding of linear algebra , calculus  and probability  are must for really understanding deep learning . It is expected that one has some knowledge or experience in basic Python programming skills with the capability to work effectively with data structures . Understanding how to frame a machine learning problem, including how data is represented will be an added advantage. Copyright @ 2015 Learntek. All Rights Reserved.

  14. Who can attend • Anyone who has coding experience with an engineering background or relevant knowledge in mathematics and computer science can take this session to get understanding of Deep learning. Copyright @ 2015 Learntek. All Rights Reserved.

  15. Copyright @ 2015 Learntek. All Rights Reserved.

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