Python Machine Learning - Class 5 | Data Exploration - Data Cleaning | Machine Learning | Edureka

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This Edureka video on 'Data Exploration - Data Cleaning' is the fifth class in the Python Machine Learning Series which gives a brief introduction to how we can clean the data from redundancies for further processes.

🟠 𝐂𝐥𝐚𝐬𝐬 𝐒𝐜𝐡𝐞𝐝𝐮𝐥𝐞 🟠

[𝗦𝗮𝘁𝘂𝗿𝗱𝗮𝘆 - 𝟭𝟱𝘁𝗵 𝗔𝘂𝗴𝘂𝘀𝘁]
Class 1 - Introduction To Machine Learning
Class 2 - Statistics For Machine Learning
Class 3 - Data Exploration 1 - ETL
Class 4 - Data Exploration 2 - Visualization
Class 5 - Data Exploration 3 - Data Cleaning
[𝐒𝐮𝐧𝐝𝐚𝐲 - 𝟏𝟔𝐭𝐡 𝐀𝐮𝐠𝐮𝐬𝐭]
Class 6 - Data Modeling 1 - Feature Engineering
Class 7 - Data Modeling 2 - Training The Model
Class 8 - Data Modeling 3 - Model Evaluation
Class 9 - Machine Learning Example
Class 10 - Advanced Machine Learning

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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 and many more.
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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.
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Who should go for this Machine Learning Certification Training using Python?
- 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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