Python for Machine Learning (ML) and Artificial Intelligence (AI)

Are you ready to unlock the potential of Python in the exciting fields of Machine Learning and Artificial Intelligence? This comprehensive course is designed to provide you with the fundamental knowledge and practical skills needed to leverage Python for building intelligent systems and retrieve data-driven insights for decision-making.

Intermediate 0(0 Ratings) 8 Students enrolled English
Created by Hut to Hut Solutions
Last updated Tue, 13-Feb-2024
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Course overview

Python is crucial in ML and AI due to its versatility, rich library ecosystem, user-friendly syntax, and community support. It offers essential tools for data manipulation, visualization, deep learning, and seamless integration, making it the preferred language for developing, researching, and deploying machine learning and AI applications.

What will i learn?

  • A firm understanding no how to perform Machine Learning (ML) and Artificial Intelligence (AI) tasks
Requirements
  • Basic knowledge of programming concepts is recommended, and prior experience with Python is helpful but not required.
Curriculum for this course
35 Lessons 03:30:26 Hours
Installation and Setup
2 Lessons 00:09:29 Hours
  • Installing Anaconda and Accessing Jupyter
    00:05:22
  • Jupyter notebook in Vs code
    00:04:07
Matplotlib for Visualization
5 Lessons 00:22:26 Hours
  • Matplotlib - Plotting Graphs in Python
    00:06:55
  • Formatting your Graphs_plots
    00:05:37
  • More charts
    00:04:27
  • Plotting a Pie Chart
    00:05:27
  • Matplotlib for Visualization
    0:00:00
Pandas - Introduction
3 Lessons 00:20:59 Hours
  • Introduction
    00:06:50
  • Common Panda Functions
    00:06:19
  • Summary Statistics
    00:07:50
Pandas - Filtering Rows and Columns
5 Lessons 00:26:22 Hours
  • Filtering Columns
    00:06:02
  • Saving filtered data to excel or csv
    00:04:29
  • Filtering Rows
    00:02:52
  • Filtering Rows with Comparison Operators
    00:07:11
  • Filtering with more than one condition
    00:05:48
Pandas - Drawing Insights from data
2 Lessons 00:14:01 Hours
  • Analyzing with the value_counts() function
    00:06:48
  • Analyzing with groupby()
    00:07:13
Pandas Series and Data frame
1 Lessons 00:12:18 Hours
  • Series and Data Frame
    00:12:18
Pandas - Course Material
1 Lessons 00:00:00 Hours
  • Datasets and Project Questions for Analysis
    .
Pandas - Quiz
1 Lessons 00:00:00 Hours
  • Pandas
    0:00:00
Introduction to NumPy
4 Lessons 00:23:01 Hours
  • Creating Arrays
    00:06:00
  • Generating Arrays
    00:06:49
  • Arithmetic and Statistical Operations of Arrays
    00:10:12
  • NumPy
    0:00:00
Building Machine Learning Models
7 Lessons 01:21:50 Hours
  • Reviewing ML Examples
    00:07:06
  • Machine Learning and Model Type Overview
    00:06:33
  • Predicting Customer Retention with H2O AutoML
    00:34:31
  • Investigating and Exporting the Model
    00:10:19
  • Overview of the Various ML Algorithms
    00:17:32
  • Resources for ML Algorithms and Implemention
    00:05:49
  • Building Machine Learning Models
    0:00:00
BUILDING MACHINE LEARNING MODELS - Course Materials
4 Lessons 00:00:00 Hours
  • Working Files
    .
  • ML Models
    .
  • Working Files - ML Models
    .
  • DS_Store
    .

Frequently asked question

Is this course suitable for beginners
this is an intermediary course, suitable for those who are familiar with Python basics
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Hut to Hut Solutions

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