- Intuitive ways to build neural networks using the PyTorch API to make this deep learning ride enjoyable
- Debug your PyTorch code using standard Python tools, so you can easily fix bugs
- Get practical, project-based experience with this popular and in-demand deep-learning library
- Master PyTorch's unique features gradually as you work through projects that make PyTorch perfect for rapid prototyping
- Work with PyTorch and learn its advantages over other frameworks, and choose the right vehicle for your deep-learning ride
- Some Python experience (and a basic understanding of ML concepts) is required.
PyTorch is grabbing the attention of all data science professionals due to its ease of use over other libraries and its use of dynamic computation graphs. Like Python, PyTorch has a clean and simple API, which makes building neural networks faster and easier.
In this course, you will learn how to accomplish useful tasks
using Convolutional Neural Networks to process spatial data such as images and
using Recurrent Neural Networks to process sequential data such as texts.
By the end of this course, you will be able to use PyTorch proficiently in your real-world projects
Job seekers looking for employment in IT companies, IT departments of PSUs or MNCs, will find the certification of great help. Certification in Deep learning with Pytorch framework benefits Data Science professionals, students and professionals
IT companies, MNCs, Consultancies hire Pytorch
professionals for Data Science related opportunities. Companies employing Data
Science include Capgemini, JP Morgan Chase, TCS, Wipro, Zensar, Accenture etc
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