Our Deep learning with Python Training helps you in mastering various features of Debugging concepts, Introduction to Software programmers, Language abilities and capacities, Modification of module and pattern designing, Various OS and compatibilities approaches.
DurationDeep Learning Using Python Training Overview
Our Deep learning with Python Training helps you in mastering various features of Debugging concepts, Introduction to Software programmers, Language abilities and capacities, Modification of module and pattern designing, Various OS and compatibilities approaches.
This course also provides Optimizing a Simple Model in Pure Theano, Convolutional and Pooling Layers , Reduce Overfitting With Dropout Regularization, Improve Generalization With Data Augmentation. Enroll & Get certified now.
Deep Learning with Python Course Curriculum:
Basic overview of the Deep Python learning
Core concepts about the programming languages
Error management and future scope
Debugging concepts
Introduction to Software programmers
Language abilities and capacities
Modification of module and pattern designing
Various OS and compatibilities approaches
Deep Learning with Python advanced strategies
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Deep learning is fast becoming among the most popular trends to be embraced by high profile companies. Powered by big data, Deep Learning has made business more viable across healthcare, genomics, cybersecurity, e-commerce, agriculture and other sectors.
The Certified Deep Learning Specialist (CDLS) course is aimed at data scientists to build complex models with human-like intelligence using Machine Learning and Deep Learning techniques.
This two-day course provides a comprehensive introduction to practical deep learning using MATLAB®. Attendees will learn how to create, train, and evaluate different kinds of deep neural networks. The instructor-led training uses NVIDIA GPUs to accelerate network training.
This certification equips students with practical industry coveted skillsets through real-life projects and subsequently transformative leadership with an end-to-end perspective on data science and machine learning.
This course introduces the pivotal components of deep learning. You learn how to build deep feedforward, convolutional, and recurrent networks.
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