Complete Supervised Machine Learning With Python

This course by industry and academic leaders is for people who want to build rewarding careers in data science.

Data science, machine learning and Python have become key industry drivers in the global job and opportunity market. This course, designed and delivered by the industry experts and Ivy League academic leaders, will help you learn supervised machine learning from scratch. You will learn the subject with lots of applications and coding using Python programming language in real life business scenarios.

What you’ll learn

  • The principle of supervised and unsupervised learning and their difference..
  • Linear and Logistic Regression, Decision Tree, Regression Tree, Random Forest, Discriminant Analysis, Support Vector Machines, Naïve Bayes Classifier, KNN.
  • How to choose the right set of algorithms and applying them in real-life projects in Python..
  • Lots of real life problem solving using Python programming language..

Course Content

  • Introduction –> 4 lectures • 14min.
  • Introduction To Python –> 5 lectures • 20min.
  • Working With Numbers In Python –> 3 lectures • 14min.
  • Handling Files In Python –> 3 lectures • 12min.
  • The NumPy Library –> 2 lectures • 11min.
  • Data Manipulation With Pandas Library In Python –> 5 lectures • 26min.
  • Data Visualization With Python –> 3 lectures • 12min.
  • Linear Regression With Python –> 5 lectures • 32min.
  • Logistic Regression With Python –> 5 lectures • 29min.
  • Complete Decision Tree With Python –> 10 lectures • 1hr 3min.
  • Regression Tree With Python –> 2 lectures • 12min.
  • Naïve Bayes Classifier And KNN With Python –> 5 lectures • 25min.
  • Random Forest With Python –> 4 lectures • 29min.
  • Discriminant Analysis With A Case Study –> 2 lectures • 21min.
  • Support Vector Machines With Python –> 4 lectures • 40min.
  • Ridge Regression –> 2 lectures • 13min.
  • Deep Learning –> 6 lectures • 55min.

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Requirements

  • You will need to have a computer or a mobile handset with an internet connection..
  • Basic knowledge of Python will be a plus..
  • Basic understanding of Statistics will be a plus..

Data science, machine learning and Python have become key industry drivers in the global job and opportunity market. This course, designed and delivered by the industry experts and Ivy League academic leaders, will help you learn supervised machine learning from scratch. You will learn the subject with lots of applications and coding using Python programming language in real life business scenarios.

In this course you will learn:

1. The principle of supervised and unsupervised learning and their difference.

2. Linear Regression, Logistic Regression, Decision Tree, Regression Tree, Random Forest, Discriminant Analysis, Support Vector Machines, Naïve Bayes Classifier, KNN with lots of real life examples using Python programming language.

3. How to choose the right set of algorithms to solve your problem statement.

 

About Spotle courses:

Spotle is an AI-powered career platform for millennial and Gen-Z population. On Spotle users get automatically matched with the most relevant opportunities and skills for the advancement of career. On the other hand, recruiters get best fit candidates on Spotle.

Spotle brings together a solid pool of machine learning and deep learning, data science, cloud computing, big data experts; The experts who have been building complex applications hands on. Spotle courses are designed by the experts to keep you updated with the in-demand trends in the market. As you move on with the Spotle courses, you learn from the experts who are passionate about new age technologies; who are keen on sharing their knowledge for the advancement of technology.

Spotle courses give you a unique opportunity to learn from and practice with the masters.