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Overview
Data Science - Deep Learning in Python from Udemy provides you with many practical examples so that you can really see how deep learning can be used on anything. Throughout the course, we'll do a course project, which will show you how to predict user actions on a website given user data like whether or not that user is on a mobile device, the number of products they viewed, how long they stayed on your site, whether or not they are a returning visitor, and what time of day they visited.
Students at Data Science - Deep Learning in Python from Udemy will:
- Learn how Deep Learning REALLY works (not just some diagrams and magical black box code)
- Learn how a neural network is built from basic building blocks (the neuron)
- Code a neural network from scratch in Python and numpy
- Code a neural network using Google's TensorFlow
- Describe different types of neural networks and the different types of problems they are used for
- Derive the backpropagation rule from first principles
- Create a neural network with an output that has K > 2 classes using softmax
- Describe the various terms related to neural networks, such as "activation", "backpropagation" and "feedforward"
- Install TensorFlow
Programme Structure
Courses include:
- Preliminaries: From Neurons to Neural Networks
- Classifying more than 2 things at a time
- Training a neural network
- Practical Machine Learning
- TensorFlow, exercises, practice, and what to learn next
- Project: Facial Expression Recognition
- Backpropagation Supplementary Lectures
- Higher-Level Discussion
Audience
- Students interested in machine learning - you'll get all the tidbits you need to do well in a neural networks course
- Professionals who want to use neural networks in their machine learning and data science pipeline. Be able to apply more powerful models, and know its drawbacks
- People who already know how to code in Python and Numpy. You will need some familiarity because we go through it quite fast.
Key information
Duration
- Part-time
- 1 days
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
Disciplines
Data Science & Big Data Artificial Intelligence Machine Learning View 144 other Short Courses in Artificial Intelligence in United StatesAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- Basic math (calculus derivatives, matrix arithmetic, probability)
- Install Numpy and Python
- Don't worry about installing TensorFlow, we will do that in the lectures.
- Being familiar with the content of my logistic regression course (cross-entropy cost, gradient descent, neurons, XOR, donut) will give you the proper context for this course
Tuition Fee
To always see correct tuition fees
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International
80 USD/fullTuition FeeBased on the tuition of 80 USD for the full programme during 1 days. -
National
80 USD/fullTuition FeeBased on the tuition of 80 USD for the full programme during 1 days.
Funding
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