Acquire a detailed understanding of the functionalities of programs like Python and Keras to work with neural networks for deep learning operations.
Neural networks, which help compensate for deep learning models, are typically built in a sequence of increasing the scale and abstraction. Neural networks are developed from a group of interconnected components that, like the synapses in the brain, can communicate with one another to function as interconnecting brain cells and understand and make decisions more like human beings. The Neural Networks in Python: Deep Learning for Beginners certification course is offered by Udemy and was designed by Start-Tech Academy, an institution of higher learning with over 160 locations worldwide.
Neural Networks in Python: Deep Learning for Beginners online course includes 9.5 hours of study material along with 4 articles, downloadable resources, practice exercises, assignments, and quizzes that revolve around topics like artificial neural networks, data processing, data manipulation, and statistical computation. Neural Networks in Python: Deep Learning for Beginners online classes also explain the functionalities of tools like Python, Keras, Tensorflow, Pandas, Numpy, and Seaborn to create neural networks for deep learning operations.
Yes
Udemy
After completing the Neural Networks in Python: Deep Learning for Beginners online certification, candidates will gain a detailed understanding of the principles and functionalities associated with neural networks including artificial neural networks. Candidates will explore the functionalities of tools like Python, Keras, and TensorFlow for deep learning activities as well as will learn about various libraries including Numpy, Pandas, and Seaborn. Candidates will gain knowledge of the techniques used in data processing, hyperparameter tuning, linear regression, and statistical computation. Additionally, candidates will learn about techniques to work with pandas data frames and Jupiter notebook.
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