2021 Machine Learning Project Course: Modelling Real Estate

Deep Learning. Google Colab , Keras. Pandas. Seaborn. Feature scaling. Matplotlib. Data Visualization. Data Scaling

Interested in the field of Machine Learning, Deep Learning and Artificial Intelligence? Then this course is for you!

What you’ll learn

  • Importing library and data, Exploratory analysis, Feature Scaling ,Data Visualization, Data Splitting, Neural Network Model, Multiple Linear Regression Model.

Course Content

  • Introduction –> 6 lectures • 34min.
  • Analysing Data –> 4 lectures • 35min.
  • Neural Network Model –> 3 lectures • 36min.
  • Bonus –> 2 lectures • 1min.
  • Thank you –> 1 lecture • 2min.

2021 Machine Learning Project Course: Modelling Real Estate

Requirements

  • No. Basic knowledge of python will be good, otherwise there is no prerequisites.

Interested in the field of Machine Learning, Deep Learning and Artificial Intelligence? Then this course is for you!

This course has been designed by a software engineer. I hope with my experience and knowledge I did gain throughout years, I can share my knowledge and help you learn complex theory, algorithms, and coding libraries in a simple way.

I will walk you step-by-step into the Machine Learning, Artificial Intelligence and Deep Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

This course is fun and exciting, but at the same time, we dive deep into Machine Learning, Deep Learning and Artificial Intelligence . Throughout the brand new version of the course we cover tons of tools and technologies including:

  • Deep Learning.
  • Google Colab
  • Artificial Neural Network.
  • Keras.
  • Pandas.
  • Seaborn.
  • Feature scaling.
  • Matplotlib.
  • Importing Data.
  • Analysing Data.
  • Exploratory Analysis.
  • Data Scaling.
  • Data Visualization.
  • Understanding Machine Learning Algorithm.
  • Splitting Data into Training Set and Test Set.
  • Training Neural Network.
  • Model building.
  • Model compilation.
  • A Comparison Of Categorical And Binary Problem.
  • Make a Prediction.
  • Testing Accuracy. 

Moreover, the course is packed with practical exercises that are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models.

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Who this course is for:

  • Anyone interested in Machine Learning.
  • Students who have at least high school knowledge in math and who want to start learning Machine Learning, Deep Learning, and Artificial Intelligence.
  • Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning, Deep Learning, Artificial Intelligence.
  • Any people who are not that comfortable with coding but who are interested in Machine Learning, Deep Learning, Artificial Intelligence and want to apply it easily on datasets.
  • Any students in college who want to start a career in Data Science.
  • Any data analysts who want to level up in Machine Learning, Deep Learning and Artificial Intelligence.
  • Any people who are not satisfied with their job and who want to become a Data Scientist.
  • Any people who want to create added value to their business by using powerful Machine Learning, Artificial Intelligence and Deep Learning tools.
  • Any people who want to work in a Real Estate sector as a Machine Learning or Deep Learning Engineer..