Complete Machine Learning & Data Science with Python | A-Z-[Udemy Machine Learning course coupon]

2 Days

Complete Machine Learning & Data Science with Python | A-Z-[Udemy 100% OFF Free Course Coupon]- Freenger.com Udemy Paid Course for Free, 100% Free Daily Course Coupon updates on Freenger.com
Topic
Machine Learning
Last Updated
26 May 2021
Brand/Type
Paid Course
Sale Price/Written By
2 Days
MRP/Available on
Udemy

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Description

Complete Machine Learning & Data Science with Python | A-Z-[Udemy 100% OFF Free Course Coupon]- Freenger.com Udemy Paid Course for Free, 100% Free Daily Course Coupon updates on Freenger.com

Hello there,

Machine learning isn’t just useful for predictive texting or smartphone voice recognition. Machine learning is constantly being applied to new industries and new problems. Whether you’re a marketer, video game designer, or programmer, my course on Udemy here to help you apply machine learning to your work.

Welcome to the “Complete Machine Learning & Data Science with Python | A-Z” course.

Do you know data science needs will create 11.5 million job openings by 2026?

Do you know the average salary is $100.000 fordata science careers!

Data Science Careers Are Shaping The Future

Data science experts are needed in almost every field, from government security to dating apps. Millions of businesses and government departments rely on big data to succeed and better serve their customers. So data science careers are in high demand.

  • If you want to learn one of the employer’s most request skills?
  • If you are curious about Data Science and looking to start your self-learning journey into the world of data with Python?
  • If you are an experienced developer and looking for a landing in Data Science!

In all cases, you are at the right place!

We’ve designed for you “Complete Machine Learning & Data Science with Python | A-Z” a straightforward course for Python Programming Language and Machine Learning.

In the course, you will have down-to-earth way explanations with projects. With this course, you will learn machine learning step-by-step. I made it simple and easy with exercises, challenges, and lots of real-life examples.

We will open the door of the Data Science and Machine Learning a-z world and will move deeper. You will learn the fundamentals of Machine Learning A-Z and its beautiful libraries such as Scikit Learn.

Throughout the course, we will teach you how to use Python to analyze data, create beautiful visualizations, and use powerful machine learning python algorithms.

This Machine Learning course is for everyone!

My “Machine Learning with Hands-On Examples in Data Science” is for everyone! If you don’t have any previous experience, not a problem! This course is expertly designed to teach everyone from complete beginners, right through to professionals ( as a refresher).

Why we use a Python programming language in Machine learning?

Python is a general-purpose, high-level, and multi-purpose programming language. The best thing about Python is, it supports a lot of today’s technology including vast libraries for Twitter, data mining, scientific calculations, designing, back-end server for websites, engineering simulations, artificial learning, augmented reality and what not! Also, it supports all kinds of App development.

What you will learn?

In this course, we will start from the very beginning and go all the way to the end of “Machine Learning” with examples.

Before each lesson, there will be a theory part. After learning the theory parts, we will reinforce the subject with practical examples.

During the course you will learn the following topics:

  • What is Machine Learning?
  • More About Machine Learning
  • Machine Learning Terminology
  • Evaluation Metrics
  • What is Classification vs Regression?
  • Evaluating Performance-Classification Error Metrics
  • Evaluating Performance-Regression Error Metrics
  • Machine Learning with Python
  • Supervised Learning
  • Cross-Validation and Bias Variance Trade-Off
  • Use Matplotlib and seaborn for data visualizations
  • Machine Learning with SciKit Learn
  • Linear Regression Theory
  • Logistic Regression Theory
  • Logistic Regression with Python
  • K Nearest Neighbors Algorithm Theory
  • K Nearest Neighbors Algorithm With Python
  • K Nearest Neighbors Algorithm Project Overview
  • K Nearest Neighbors Algorithm Project Solutions
  • Decision Trees And Random Forest Algorithm Theory
  • Decision Trees And Random Forest Algorithm With Python
  • Decision Trees And Random Forest Algorithm Project Overview
  • Decision Trees And Random Forest Algorithm Project Solutions
  • Support Vector Machines Algorithm Theory
  • Support Vector Machines Algorithm With Python
  • Support Vector Machines Algorithm Project Overview
  • Support Vector Machines Algorithm Project Solutions
  • Unsupervised Learning Overview
  • K Means Clustering Algorithm Theory
  • K Means Clustering Algorithm With Python
  • K Means Clustering Algorithm Project Overview
  • K Means Clustering Algorithm Project Solutions
  • Hierarchical Clustering Algorithm Theory
  • Hierarchical Clustering Algorithm With Python
  • Principal Component Analysis (PCA) Theory
  • Principal Component Analysis (PCA) With Python
  • Recommender System Algorithm Theory
  • Recommender System Algorithm With Python

With my up-to-date course, you will have a chance to keep yourself up-to-date and equip yourself with a range of Python programming skills. I am also happy to tell you that I will be constantly available to support your learning and answer questions.

Why would you want to take this course?

Our answer is simple: The quality of teaching.

OAK Academy based in London is an online education company. OAK Academy gives education in the field of IT, Software, Design, development in English, Portuguese, Spanish, Turkish, and a lot of different languages on the Udemy platform where it has over 1000 hours of video education lessons. OAK Academy both increases its education series number by publishing new courses, and it makes students aware of all the innovations of already published courses by upgrading.

When you enroll, you will feel the OAK Academy`s seasoned developers’ expertise. Questions sent by students to our instructors are answered by our instructors within 48 hours at the latest.

Video and Audio Production Quality

All our videos are created/produced as high-quality video and audio to provide you the best learning experience.

You will be,

  • Seeing clearly
  • Hearing clearly
  • Moving through the course without distractions

You’ll also get:

  • Lifetime Access to The Course
  • Fast & Friendly Support in the Q&A section
  • Udemy Certificate of Completion Ready for Download

We offer full support, answering any questions.

If you are ready to learnthe “Complete Machine Learning & Data Science with Python | A-Z” course.

Dive in now! See you in the course!

Who this course is for:

  • Machine learning isn’t just useful for predictive texting or smartphone voice recognition. Machine learning is constantly being applied to new industries and new problems. It is for everyone
  • Anyone who wants to start learning “Machine Learning”
  • Anyone who needs a complete guide on how to start and continue their career with machine learning
  • Software developer who wants to learn “Machine Learning”
  • Students Interested in Beginning Data Science Applications in Python Environment
  • People Wanting to Specialize in Anaconda Python Environment for Data Science and Scientific Computing
  • Students Wanting to Learn the Application of Supervised Learning (Classification) on Real Data Using Python

Additional Info

What you'll learn

  • Machine learning isn’t just useful for predictive texting or smartphone voice recognition. Machine learning is constantly being applied to new industries and new problems. Whether you’re a marketer, video game designer, or programmer, my course on Udemy will help you apply machine learning to your work.
  • Learn Machine Learning with Hands-On Examples
  • What is Machine Learning?
  • Machine Learning Terminology
  • Evaluation Metrics
  • What are Classification vs Regression?
  • Evaluating Performance-Classification Error Metrics
  • Evaluating Performance-Regression Error Metrics
  • Supervised Learning
  • Cross Validation and Bias Variance Trade-Off
  • Use matplotlib and seaborn for data visualizations
  • Machine Learning with SciKit Learn
  • Linear Regression Algorithm
  • Logistic Regresion Algorithm
  • K Nearest Neighbors Algorithm
  • Decision Trees And Random Forest Algorithm
  • Support Vector Machine Algorithm
  • Unsupervised Learning
  • K Means Clustering Algorithm
  • Hierarchical Clustering Algorithm
  • Principal Component Analysis (PCA)
  • Recommender System Algorithm

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