82% Off Automated Machine Learning with AutoGluon Library in Python | Udemy Review & Coupon

Learn how to automate machine learning pipelines effortlessly with the Autogluon library, which is highly potent and developed by AWS.

This course covers:

AutoGluon, an automated machine learning library for Python, is now available with 5.5 hours of on-demand video, four articles, and three downloadable resources. This means that anyone can learn the basics of machine learning easily and quickly from anywhere at any time. The content is viewable on mobile devices and TVs, so users can tailor their experience to their convenience. The course also includes a certificate of completion, making it a great way to show off your skills and learn something new.

What you'll learn

The Autogluon Python Library is an open-source project that enables users to automate their machine learning tasks. It utilizes the power of deep learning to make predictive analytics and data-driven decisions easier and faster to obtain. With this library, you can quickly set up a local environment and build models with minimal effort, while still achieving maximum accuracy. First, you’ll need to understand the basics of Autogluon to maximize your success rate for any given task. This includes general concepts such as learning how to install and configure the library, preparing datasets for machine learning algorithms, selecting appropriate ML models, and more. Additionally, you can learn best practices for accurately performing tasks such as image classification, object detection, semantic segmentation, and language processing (NLP), among other procedures. Each task requires different approaches by taking advantage of the most suitable model architectures the library has to offer in order to achieve top results. Autogluon handles all of these complexities for you behind the scenes so that its users can easily create highly accurate AI solutions without having extensive training or expertise in ML engineering.

About the author

Jose Portilla is a highly sought-after Data Science, Machine Learning, and Python Programming instructor. A veteran educator with both an MS and BS in Mechanical Engineering from Santa Clara University, Jose has a diverse background in data science and can help anyone get started on the journey of learning programming. With experience in microfluidics, materials science, data science, and more fields to his name, he brings real-world experience to the classroom - offering hands-on insight into applying data analytics as well as teaching visual presentation of results.

As the Head of Data Science for Pierian Training, Jose has helped many professionals further their training with courses tailored for those working at top companies - including General Electric, Cigna, The New York Times, Credit Suisse, and McKinsey. With so much knowledge at his disposal, Jose’s classes are not only fun but also full of practical applications that leave students feeling empowered by their new skillset. If you’re looking to pursue data science seriously be sure to check out Pierian Training's website for more information on their training capabilities.

Requirements

Requirements for a certain role can vary depending on the company or position. In this case, the requirements include some Python experience. This is an extremely important qualification as many companies use Python to develop their programs and software. It shows that the candidate is familiar with how to code reliably, efficiently, and to industry standards.

Additionally, previous machine learning experience is not required but is considered helpful by the employer.

Description

Autogluon is a powerful Python library designed to automate machine learning tasks and achieve strong predictive performance in your applications. This comprehensive online course provides you with the skills and knowledge needed to use it effectively. With Autogluon, you can significantly reduce the time and labor required to train machine learning models by coding just a few lines. You can then deploy high-accuracy models to tackle image, text, time series, and tabular data quickly and easily.

The course covers a variety of topics related to Autogluon such as hyperparameter optimization strategies, neural networks building blocks, automated deep learning feature engineering, distributed training frameworks, tuning algorithms hyperparameters with Bayesian optimization, deploying models on cloud infrastructure, data preprocessing techniques for various kinds of datasets and more. This will enable the learner with the foundational knowledge of using Autogluon for automating their machine learning tasks effectively.

With Autogluon, you can create high-quality models with minimal effort. The library provides a rich set of features that make it easy to build powerful algorithms quickly and effectively. Autogluon’s AutoML capabilities enable users to choose the right hyperparameters for each task without having to manually tune them. This allows you to find optimal settings for your model in a fraction of the time required for manual tuning.

This course is intended for:

This course is designed for data scientists, machine learning engineers, and software developers who are looking to efficiently automate their machine learning tasks. Fundamentals of automation have become an important part of the workflow for these professionals in order to keep up with the rapidly changing landscape of technology and make sure that they’re bringing the best value possible to their companies.