Learn Automated Machine Learning : Build Real World Projects

Solve Data Science Problems Using Automated -ML, Learn To Use Eval ML, Pycaret, Auto Keras, Auto SK Learn, H20 Auto ML
What you'll learn
Learn to perform Classification and Regression modelling
Implement Machine Learning algorithms
Master Machine Learning and use it on the job
Write clean, maintainable and performant code
Use Seaborn to create beautiful statistical plots with Python.
Learn how to use Scikit-learn to apply powerful machine learning algorithms.
Get set-up quickly with the Anaconda data science stack environment.
Learn best practices when it comes to Data Science Workflow
Requirements
Knowledge Of Machine Learning
Description
Automated Machine Learning provides methods and processes to make Machine Learning available for non-Machine Learning experts, to improve efficiency of Machine Learning and to accelerate research on Machine Learning.
Machine learning (ML) has achieved considerable successes in recent years and an ever-growing number of disciplines rely on it. However, this success crucially relies on human machine learning experts to perform the following tasks:
Preprocess and clean the data.
Select and construct appropriate features.
Select an appropriate model family.
Optimize model hyperparameters.
Design the topology of neural networks (if deep learning is used).
Postprocess machine learning models.
Critically analyze the results obtained.
As the complexity of these tasks is often beyond non-ML-experts, the rapid growth of machine learning applications has created a demand for off-the-shelf machine learning methods that can be used easily and without expert knowledge. We call the resulting research area that targets progressive automation of machine learning AutoML
You can think of machine learning as a subset of artificial intelligence technologies, as it involves training a machine to learn more quickly and more intelligently.
Where AI technology focuses on mimicking human intelligence, allowing computers to learn from experience, machine learning focuses on making them learn more, and faster, from that experience.
In a way, machine learning is like an optimization process for AI technologies, with the machine learning engineer being responsible for providing better, faster training to AI solutions.
The goal of the machine learning process is to make AI solutions faster and smarter so they can deliver even better results for whatever task they’ve been set to achieve.
Because AI technology is capable of having such a huge impact on society and modern business practices, revolutionizing everyday tasks from planning to logistics to operations and production, machine learning experts are in extremely high demand.

Who this course is for:
Beginners in machine learning

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