***** Python Certification Training for Data Science : https://www.edureka.co/python *****
This Edureka video on “Machine Learning Tutorial” will help you get started with all the Machine Learning concepts. Below are the topics covered in this video:
1. Why Machine Learning?
2. What is Machine Learning?
3. Types of Machine Learning
4. What can you do with Machine Learning?
5. Machine Learning Demo in Python
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Machine Learning Tutorial Playlist: https://goo.gl/UxjTxm
#DataScience #MachineLearningTutorial #MachineLearningAlgorithm
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About the Course
Edureka’s Python Certification Training not only focuses on fundamentals of Python, Statistics and Machine Learning but also helps one gain expertise in applied Data Science at scale using Python. The training is a step by step guide to Python and Data Science with extensive hands on. The course is packed with several activity problems and assignments and scenarios that help you gain practical experience in addressing predictive modeling problem that would either require Machine Learning using Python. Starting from basics of Statistics such as mean, median and mode to exploring features such as Data Analysis, Regression, Classification, Clustering, Naive Bayes, Cross Validation, Label Encoding, Random Forests, Decision Trees and Support Vector Machines with a supporting example and exercise help you get into the weeds.
Furthermore, you will be taught of Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to train your machine based on real-life scenarios using Machine Learning Algorithms.
Edureka’s Python course will also cover both basic and advanced concepts of Python like writing Python scripts, sequence and file operations in Python. You will use libraries like pandas, numpy, matplotlib, scikit, and master the concepts like Python machine learning, scripts, and sequence.
After completing this Data Science Certification training, you will be able to:
1. Programmatically download and analyze data
2. Learn techniques to deal with different types of data – ordinal, categorical, encoding
3. Learn data visualization
4. Using I python notebooks, master the art of presenting step by step data analysis
5. Gain insight into the ‘Roles’ played by a Machine Learning Engineer
6. Describe Machine Learning
7. Work with real-time data
8. Learn tools and techniques for predictive modeling
9. Discuss Machine Learning algorithms and their implementation
10. Validate Machine Learning algorithms
11. Explain Time Series and its related concepts
12. Perform Text Mining and Sentimental analysis
13. Gain expertise to handle business in future, living the present
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Why learn Python for Data Science?
It’s continued to be a favourite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging programs is a breeze in Python with its built in debugger.
It runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license.
It has evolved as the most preferred Language for Data Analytics and the increasing search trends on Python also indicates that it is the ” Next Big Thing ” and a must for Professionals in the Data Analytics domain.
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