What's Included

  • 12:22:46 on-demand video
  • 111 Lectures
  • 26 Assignments
  • 12 Quizzes
  • Access on tablet and phone

Preview

What you'll learn

  • Python
  • Jupyter Notebook
  • Numpy
  • Pandas
  • Matplotlib for data visualization
  • Machine Learning using sklearn
  • Deep learning using tensorflow 2.0

Course Curriculum

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111 Lectures

12:22:46

Machine Learning Tutorial Python 43 Lectures
Data Science & Machine Learning Project - Image Classification 8 Lectures
Deep Learning Tutorial 45 Lectures

Description

We will understand what is data science by looking at simple restaurant business example. Data science is a process of getting insights from data. You don't have to be deep learning expert in order to do data science, you can do that in plain old microsoft excel also (if dataset is small enough). In recent years volume of data has grown too much so that data has become BIG DATA. Microsoft excel can't work with big data hence you need tools such as,

1) Apache hadoop and apache spark: For database storage and distributed computing
2) Python and R: For data science programming
3) Tableau, Power BI, Matplotlib, MATLAB, Jupyter Notebook: For data visualization
4) Sklearn, Deep Learning, Tensorflow, PyTorch: For deep learning and machine learning

Data scientist has become the most popular job in the market today and there is a huge career scope if you know how to do data science. Some of the use cases of data science in real life are,

1) Healthcare: Diagnostic prediction and accuracy
2) Finance: Fraud detection, predictive analysis on loans, stock market movement, company future
3) Shipping: Figure out best route for shipping 
4) E-commerce: Product recommendation, inventory pricing

Instructor

(4.7)

44 Courses

Student feedback

5.0

From 2 Reviews

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This course is amazing and the instructor explain it on a simple and clear way that anybody can understand.

Do you have also the following courses
- Machine Learning?
- Deep Learning?
- Artificial Intelligence?
- Computer Vision?
- Bitcoin

Big thanks for this course...
Very clearly explained and intuitively