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Machine Learning from the scratch using Python
Rating: 4.1 out of 5(90 ratings)
2,399 students

Machine Learning from the scratch using Python

Machines are now learning, why aren't you?
Created bySaheb Singh Chaddha
Last updated 4/2020
English

What you'll learn

  • Great knowledge of Machine Learning and Deep Learning Algorithms.
  • Work on real case studies
  • 5 projects to work on which can be easily put up on resume for better placements.
  • Build your own ML Algorithm, Models and Predictions.
  • Hands-on Numpy, Panda, Matplotlib, etc and many more

Course content

2 sections • 35 lectures • 15h 2m total length

  • Introduction to Python in Data Science8:41

    This lecture introduces data science fundamentals, highlights Python as the primary tool, covers statistics, machine learning, deep learning, natural language processing, and guides installing Anaconda and launching Jupyter notebooks.

  • Arithmetic Functions10:02
  • Defining, Storing Variables and Datatypes8:41
  • Working with Data Types9:35
  • PRACTICE8:36
  • Introduction to Lists7:25
  • SLICING6:42
  • Accessing List Values7:24

    Access list values by index using square brackets, learn zero-based indexing, and explore both positive and negative indexes.

  • Sub-setting Lists7:13
  • Advanced List Operations7:08
  • Built in Functions 1.15:55

    Explore built-in Python functions, call them with examples like print, convert strings to int and float, and use max or min to process data.

  • Built in Functions 1.26:29

    learn to use the built-in max and min functions to find the largest or smallest value in a list, and evaluate expressions from inside out.

  • Function Arguments 1.18:28
  • Function Arguments 1.28:35
  • Introduction to String Methods 1.17:00
  • Introduction to String Methods 1.27:09

    This lecture introduces Python string methods, demonstrates indexing to locate substrings, using find and index for first occurrences, and applying lower and upper case transformations.

  • Importing Python Packages9:06
  • Introduction to String Methods 1.37:49
  • Subsetting and Comparing Arrays 1.18:26

    Explore subsetting arrays by index and using operators like less than, greater than, and equal to to print boolean results for each element.

  • Introduction to NumPy Arrays7:22
  • Subsetting and Comparing Arrays 1.27:56

Requirements

  • Basic Python, Mathematics and Statistics

Description

This course is for those who want to step into Artificial Intelligence domain, specially into Machine Learning, though I will be covering Deep Learning in deep as well.

This is a basic course for beginners, just if you can get basic knowledge of Python that would be great and helpful to you to grasp things quickly. 

There are 4-5 Projects on real data set which will be very helpful to start your career in this domain, Right now if you don't see the project, don't panic, it might have gone old so I've put it down for modifications.


Enjoy and Good Luck.


Who this course is for:

  • Beginner or Stepping into AI, ML, DL domain with 4-5 Projects on real data set.

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