Overview
Key Facts
The Introduction to Machine Learning with TensorFlow course is delivered at Udacity . Start with foundational supervised learning algorithms including linear regression, decision trees, naive Bayes, support vector machines (SVMs), and perceptrons, then evaluate your model performance with a variety of evaluation metrics. Then you'll advance from perceptrons to deep neural networks in order to perform supervised learning on complex data sources such as images. Finally, you'll dive into unsupervised learning methods, including clustering and dimensionality reduction for customer segmentation. For each technique, you'll start by learning the underlying math, then implement real-world models with Python libraries including TensorFlow and scikit-learn.
Get more details
Visit programme websiteProgramme Structure
Courses include:
- Supervised Learning
- Neural Networks with TensorFlow
- Unsupervised Learning
- Prerequisite: Python for Data Analysis
- Prerequisite: SQL for Data Analysis
Check out the full curriculum
Visit programme websiteKey information
Duration
- Part-time
- 2 months
- Flexible
Start dates & application deadlines
Language
Delivered
Campus Location
- Mountain View, United States
Disciplines
Web Technologies & Cloud Computing Machine Learning View 558 other preparation in Web Technologies & Cloud Computing in United StatesExplore more key information
Visit programme websiteWhat students do after studying
Academic 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
To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:
- Basic descriptive statistics
- Data wrangling
- Python for data science
- Basic probability
- Basic calculus
- Linear algebra
- Intermediate Python
- Basic supervised machine learning
- Multivariable calculus
You will also need to be able to communicate fluently and professionally in written and spoken English.
Make sure you meet all requirements
Visit programme websiteTuition Fees
-
International Applies to you
Applies to youNon-residents249 USD / module≈ 249 USD / module - Out-of-State249 USD / module≈ 249 USD / module
Additional Details
249$ - Monthly Subscription - Unlimited access to all Udacity programs, skills and projects
Funding
In order for us to give you accurate scholarship information, we ask that you please confirm a few details and create an account with us.
Scholarships Information
Below you will find Master's scholarship opportunities for Introduction to Machine Learning with TensorFlow.
Available Scholarships
You are eligible to apply for these scholarships but a selection process will still be applied by the provider.
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility