10 Machine Learning Algorithms to Know in 2025
January 28, 2025
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Learn to build AI apps with Tensorflow. Build, train, and optimize deep neural networks and dive deep into Computer Vision, Natural Language Processing, and Time Series Analysis, along with best practices and hands-on experience in one of the most in-demand deep learning frameworks.
Instructor: Laurence Moroney
213,004 already enrolled
(21,704 reviews)
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Intermediate level
Experience in Python coding and high school-level math is required. Prior machine learning or deep learning knowledge is helpful but not required.
(21,704 reviews)
Recommended experience
Intermediate level
Experience in Python coding and high school-level math is required. Prior machine learning or deep learning knowledge is helpful but not required.
Best practices for TensorFlow, a popular open-source machine learning framework to train a neural network for computer vision applications.
Handle real-world image data and explore strategies to prevent overfitting, including augmentation and dropout.
Build natural language processing systems using TensorFlow.
Apply RNNs, GRUs, and LSTMs as you train them using text repositories.
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TensorFlow is one of the most in-demand and popular open-source deep learning frameworks available today. The DeepLearning.AI TensorFlow Developer Professional Certificate program teaches you applied machine learning skills with TensorFlow so you can build and train powerful models.
In this hands-on, four-course Professional Certificate program, you’ll learn the necessary tools to build scalable AI-powered applications with TensorFlow. After finishing this program, you’ll be able to apply your new TensorFlow skills to a wide range of problems and projects. This program can help you prepare for the Google TensorFlow Certificate exam and bring you one step closer to achieving the Google TensorFlow Certificate.
Ready to deploy your models to the world? Learn how to go live with your models with the TensorFlow: Data and Deployment Specialization.
Looking to customize and build powerful real-world models for complex scenarios? Check out the TensorFlow: Advanced Techniques Specialization.
Applied Learning Project
In the DeepLearning.AI TensorFlow Developer Professional Certificate program, you'll get hands-on experience through 16 Python programming assignments. By the end of this program, you will be ready to:
- Build and train neural networks using TensorFlow
- Improve your network’s performance using convolutions as you train it to identify real-world images
- Teach machines to understand, analyze, and respond to human speech with natural language processing systems
- Process text, represent sentences as vectors, and train a model to create original poetry!
- Create forecasts for univariate time series using deep neural networks
Learn best practices for using TensorFlow, a popular open-source machine learning framework
Build a basic neural network in TensorFlow
Train a neural network for a computer vision application
Understand how to use convolutions to improve your neural network
Handle real-world image data
Plot loss and accuracy
Explore strategies to prevent overfitting, including augmentation and dropout
Learn transfer learning and how learned features can be extracted from models
Build natural language processing systems using TensorFlow
Process text, including tokenization and representing sentences as vectors
Apply RNNs, GRUs, and LSTMs in TensorFlow
Train LSTMs on existing text to create original poetry and more
Solve time series and forecasting problems in TensorFlow
Prepare data for time series learning using best practices
Explore how RNNs and ConvNets can be used for predictions
Build a sunspot prediction model using real-world data
DeepLearning.AI is an education technology company that develops a global community of AI talent. DeepLearning.AI's expert-led educational experiences provide AI practitioners and non-technical professionals with the necessary tools to go all the way from foundational basics to advanced application, empowering them to build an AI-powered future.
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Yes, if you paid a one-time $49 payment for one or more of the courses, you can still subscribe to the Specialization for $49/month. If you pay for one course, you will have access to it for 180 days, or until you complete the course. If you subscribe to the Specialization, you will have access to all four courses until you end your subscription.
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Certificate, you’re automatically subscribed to the full Certificate. Visit your learner dashboard to track your progress.
¹Based on Coursera learner outcome survey responses, United States, 2021.