COURSE DESCRIPTION
For deep learning tasks, PyTorch is a well-liked open-source machine learning package. The AI Research lab at Facebook created it, and it provides a dynamic and adaptable computational framework for neural network construction. The primary advantage of PyTorch is its dynamic computing graph, which makes debugging and model creation more straightforward. It can be used with a variety of hardware configurations because it supports both CPU and GPU acceleration. PyTorch makes work easier by providing a vast ecosystem of modules and tools for activities like data processing and model deployment. For artificial intelligence researchers and developers, its user-friendly interface and robust community support make it a top option. Learn about our other post at codingshikho.com
CERTIFICATION
We will begin by teaching you How to develop apps with the help of our course Once you gain confidence in building and developing apps using pytorch , then we’ll proceed with Paid version of this pytorch and designing. and then you are provided with certificate.
We will Cover the following Topics in my sessions : –
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from Coding Shikho
you would be able to build & design Your apps using pytorch that secures Top Positions in the Google search Results!
Requirements
- Python:
PyTorch is primarily a Python library, so you should have a good understanding of Python. If you're new to Python, start with the basics of the language, including variables, data types, loops, and functions.
- Mathematics and Linear Algebra:
Deep learning involves a lot of mathematical concepts, especially linear algebra. Understanding matrix operations, vectors, and basic calculus is crucial. Familiarity with concepts like derivatives and gradients is important for understanding neural network training.
- Machine Learning Fundamentals:
It's beneficial to have a fundamental understanding of machine learning concepts, such as supervised and unsupervised learning, classification, regression, and evaluation metrics.
- Deep Learning Basics:
Knowledge of deep learning principles, such as neural networks, activation functions, forward and backward propagation, and loss functions, is essential. You can start by learning the basics of neural networks and their components.
- Projects and Practice:
Apply what you've learned by working on small projects and Kaggle competitions. Hands-on experience is crucial for mastering PyTorch.
Features
- Instructor-Well-qualified and we choose them from industry. .
- Placement- 100%
- Residential room- well- Air-conditioned room , good food Availability, cloth cleaning services
- Project- Real world projects to learn and develops skills .
- Material - PDF , 90h classes, Friendly-environment and Videos .
Target audiences
- Gender- Male & Female
- Age- 15y to 60y
- Qualification- BCA, MCA ,B.Tech and B.Sc
- Hobbies- Interested in learning , problem solving , practicing and reading
- Experience - 0y-1y