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Deep Learning
Deep learning is driving advances in artificial intelligence (AI) that are changing our world to improve our vision in using data. Enroll now to this course to build and apply your own deep neural networks skills to produce amazing solutions to important challenges.
WHY ENROLL
Become career-ready faster
INDUSTRY SIZE & DEMAND
Deep Learning Market is trending and expected to grow at the CAGR of 52.1% till 2025
JOB OPPORTUNITIES
Demand for AI, DL and ML specialists in the country are expected to see a 60% rise by 2018 due to increasing adoption of automation
RANKED #08 CNBC
Udacity ranked as the most disruptive learning company in the world for past 2 years in a row by CNBC which really makes it worth
Prerequisites and Requirements
It is recommended to have intermediate experience in Python to start this program. Some basic knowledge of machine learning is beneficial, but it is not required to start this program as it will start with basics.
Prepare now with AI Programming with Python.
WHAT YOU LEARN
Study cutting edge Content
Deep Learning Nanodegree
In this term, you’ll build and apply your own deep neural networks to produce amazing solutions to important challenges.
COURSE SYLLABUS
Introduction
In starting of deep learning course you will apply style transfer to your own images, and gain experience using development tools such as Anaconda and Jupyter notebooks.
Neural Networks
Learn neural networks basics, and build your first network with Python and NumPy which is a real fun. Use the modern deep learning framework PyTorch to build multi-layer neural networks and analyze real datasets.
Convolutional Neural Networks
Get to know how to build convolutional networks and using them to classify images (faces, melanomas, etc.) based on patterns and objects that appear in themto get a deep understanding of it. T
Recurrent Neural Networks
Learn to build your own recurrent networks and long short-term memory networks with PyTorch to perform sentiment analysis and use recurrent networks to generate new text from TV scripts.
Deploying a Sentiment Analysis Model
Train and deploy PyTorch sentiment analysis model. Deployment gives the ability to use a trained model to analyze new user input. Build a model, test it, deploy it and create a gateway for accessing it from a website.
In starting of deep learning course you will apply style transfer to your own images, and gain experience using development tools such as Anaconda and Jupyter notebooks.
Neural Networks
Learn neural networks basics, and build your first network with Python and NumPy which is a real fun. Use the modern deep learning framework PyTorch to build multi-layer neural networks and analyze real datasets.
Convolutional Neural Networks
Get to know how to build convolutional networks and using them to classify images (faces, melanomas, etc.) based on patterns and objects that appear in themto get a deep understanding of it. T
Recurrent Neural Networks
Learn to build your own recurrent networks and long short-term memory networks with PyTorch to perform sentiment analysis and use recurrent networks to generate new text from TV scripts.
Deploying a Sentiment Analysis Model
Train and deploy PyTorch sentiment analysis model. Deployment gives the ability to use a trained model to analyze new user input. Build a model, test it, deploy it and create a gateway for accessing it from a website.
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