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The Complete Machine Learning 2021 : 10 Real World Projects

 

The Complete Machine Learning 2021 : 10 Real World Projects

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What you'll learn

  • Python
  • Machine Learning
  • Statistics and Math
  • Data Science
  • Natural Language Processing
  • Data Analysis
  • Data Visualization

Requirements

  • Motivation to Learn

Description

Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world’s most interesting problems!

This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science!

This course is made to give you all the required knowledge at the beginning of your journey, so that you don’t have to go back and look at the topics again at any other place. This course is the ultimate destination with all the knowledge, tips and trick you would require to start your career.

It gives detailed guide on the Data science process involved and Machine Learning algorithms. All the algorithms are covered in detail so that the learner gains good understanding of the concepts. Although Machine Learning involves use of pre-developed algorithms one needs to have a clear understanding of what goes behind the scene to actually convert a good model to a great model.

Our exotic journey will include the concepts of:

  1. Comparison between Artificial intelligence, Machine Learning, Deep Learning and Neural Network.
  2. What is data science and its need.
  3. The need for machine Learning and introduction to NLP (Natural Language Processing).
  4. The different types of Machine Learning – Supervised and Unsupervised Learning.
  5. Hands-on learning of Python from beginner level so that even a non-programmer can begin the journey of Data science with ease.
  6. All the important libraries you would need to work on Machine learning lifecycle.
  7. Full-fledged course on Statistics so that you don’t have to take another course for statistics, we cover it all.
  8. Data cleaning and exploratory Data analysis with all the real life tips and tricks to give you an edge from someone who has just the introductory knowledge which is usually not provided in a beginner course.
  9. All the mathematics behind the complex Machine learning algorithms provided in a simple language to make it easy to understand and work on in future.
  10. Hands-on practice on more than 20 different Datasets to give you a quick start and learning advantage of working on different datasets and problems.
  11. More that 20 assignments and assessments allow you to evaluate and improve yourself on the go.
  12. Total 10 beginner to Advance level projects so that you can test your skills.

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