Cross-Validation In Machine Learning | ML Fundamentals | Machine Learning Tutorial | Edureka

Описание: ** Machine Learning Certification Training: https://www.edureka.co/machine-learni... **
This Edureka Video on 'Cross-Validation In Machine Learning' covers A brief introduction to Cross-Validation with its various types, limitations, and applications. Following are the topics discussed in this Machine Learning Tutorial Video:

What is Cross-Validation In Machine Learning?
Types Of Cross-Validation
Cross-Validation API
How To Measure Model's Bias-Variance
Limitations Of Cross-Validation
Cross-Validation Applications

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How it Works?

Edureka’s Machine Learning Course using Python is designed to make you grab the concepts of Machine Learning. Machine Learning training will provide a deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in the python programming language. Furthermore, you will be taught of Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real-life scenarios using Machine Learning Algorithms. Towards the end of the course, we will be discussing various practical use cases of Machine Learning in the python programming language to enhance your learning experience.

Why Learn Machine Learning using Python?

Data Science is a set of techniques that enables computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning.

After completing this Machine Learning Certification Training using Python, you should be able to:
Gain insight into the 'Roles' played by a Machine Learning Engineer
Automate data analysis using python
Describe Machine Learning
Work with real-time data
Learn tools and techniques for predictive modeling
Discuss Machine Learning algorithms and their implementation
Validate Machine Learning algorithms
Explain Time Series and it’s related concepts
Gain expertise to handle business in the future, living the present
Who should go for this Machine Learning Certification Training using Python?

Edureka’s Python Machine Learning Certification Course is a good fit for the below professionals:
Developers aspiring to be a ‘Machine Learning Engineer'
Analytics Managers who are leading a team of analysts
Business Analysts who want to understand Machine Learning (ML) Techniques
Information Architects who want to gain expertise in Predictive Analytics
'Python' professionals who want to design automatic predictive models

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