3 Best Tensorflow Specialization Courses You should Take in 2020/2021
Tensorflow is one of the most famous Machine Learning libraries currently. It might be difficult to understand at the beginning but its abilities are tremendous.
It’s a powerful machine learning framework that may be your new closest companion on the off chance that you have a great deal of information as well as you’re after the best in class in AI.
In this post, I’ll review the most famous TensorFlow specialization courses on Coursera associated with Tensorflow.
Here’s the list of the best Tensorflow specialization courses on Coursera:
- DeepLearning.AI TensorFlow Developer Professional Certificate by deeplearning.ai
- Machine Learning with TensorFlow on Google Cloud Platform Specialization by Google
- TensorFlow: Data and Deployment Specialization by deeplearning.ai
Let’s now review them one after the other.
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.
There are four Courses in this Professional Certificate:
- Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
- Convolutional Neural Networks in TensorFlow
- Natural Language Processing in TensorFlow
- Sequences, Time Series, and Prediction
Course Objectives:
- 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!
2. Machine Learning with TensorFlow on Google Cloud Platform Specialization
This course is focused on using the flexibility and “ease of use” of TensorFlow 2.x and Keras to build, train, and deploy machine learning models. You will learn about the TensorFlow 2.x API hierarchy and will get to know the main components of TensorFlow through hands-on exercises. We will introduce you to working with datasets and feature columns. You will learn how to design and build a TensorFlow 2.x input data pipeline. You will get hands-on practice loading csv data, NumPy arrays, text data, and images using tf.Data.Dataset. You will also get hands-on practice creating numeric, categorical, bucketized, and hashed feature columns.
There are six Courses in this Professional Certificate:
- How Google does Machine Learning
- Launching into Machine Learning
- Introduction to TensorFlow
- Feature Engineering
- Art and Science of Machine Learning
Course Objectives:
- Frame a business use case as a machine learning problem.
- Convert a candidate use case to be driven by machine learning
- Gain a broad perspective of machine learning and where it can be used
- Use the Keras Sequential and Functional APIs for simple and advanced model creation
3. TensorFlow: Data and Deployment Specialization
In this Specialization, you’ll learn how to get your machine learning models into the hands of real people on all kinds of devices. Start by understanding how to train and run machine learning models in browsers and mobile applications. Learn how to leverage built-in datasets with just a few lines of code, learn about data pipelines with TensorFlow data services, use APIs to control data splitting, process all types of unstructured data, and retrain deployed models with user data while maintaining data privacy. Apply your knowledge in various deployment scenarios and get introduced to TensorFlow Serving, TensorFlow, Hub, TensorBoard, and more.
There are four Courses in this specialization:
- Browser-based Models with TensorFlow.js
- Device-based Models with TensorFlow Lite
- Data Pipelines with TensorFlow Data Services
- Advanced Deployment Scenarios with TensorFlow
Course Objectives:
- Run models in your browser using TensorFlow.js
- Prepare and deploy models on mobile devices using TensorFlow Lite
- Access, organize, and process training data more easily using TensorFlow Data Services
- Explore four advanced deployment scenarios using TensorFlow Serving, TensorFlow Hub, and TensorBoard
Summary
Those specializations noted above are among the most famous on Coursera in relation to Tensorflow, you should sense free to explore greater of them.
