Machine Learning Using Python

Overview

Course Description

This course is designed for those interested in learning more about machine learning and how to apply it to different business problems. This course is geared toward intermediate Python programmers and covers machine-learning concepts and techniques.

What you'll learn

You should learn Machine Learning Using Python course covers theoretical and practical aspects of machine learning.
How to use course covers supervised and unsupervised algorithms.
How to use Python libraries for this purpose is TensorFlow, which can be used for deep and recurrent neural networks.

How to Use the TensorFlow framework, you can build neural networks, reinforcement learning, and natural language processing models.
How to use OpenCV, an open-source computer vision library written in C/C++.
You can learn about linear, Non-linear, simple and multiple regression and their applications.

Course Content

Advanced Python

Lecture 1.1 Overview of Python language

02:53
Lecture 1.2 Programming Constructs

02:53
Lecture 1.3 Python Functions

02:53
Lecture 1.4 Modules and Packages

02:53
Lecture 1.5 Broadcasting and numpy functions

02:53
Lecture 1.6 Pandas Library

02:53
Lecture 1.7 Visualization using matplotlib and Seaborn

02:53

Machine Learning

Lecture 2.1 Categories of ML

02:53
Lecture 2.2 Supervised Learning Models

02:53
Lecture 2.3 Ensemble Methods of Classification

02:53
Lecture 2.4 Machine Learning Evaluation Metrics

02:53
Lecture 2.5 Cross Validation

02:53

Computer Vision

Lecture 3.1 Introduction to Computer Vision

02:53
Lecture 3.2 Face Recognition and Detection with OpenCV

02:53
Lecture 3.3 Face Recognisers, Training data, Prediction

02:53

Deep Learning

Lecture 4.1 Artificial Neural Networks and Model

02:53
Lecture 4.2 ANN structure, Feed Forward Neural network

02:53
Lecture 4.3 Back Propagation, Deep Learning Concepts

02:53
Lecture 4.4 Convolution Neural Network (CNN)

02:53
Lecture 4.5 Neural Network using TensorFlow

02:53

Natural Language Processing

Lecture 5.1 Basics of text processing

02:53
Lecture 5.2 NLP tasks in syntax, semantics, and pragmatics

02:53
Lecture 5.3 Applications like Automatic Summarization

02:53
Lecture 5.4 Sentiment Analysis and Text Classification

02:53

About Us

TECHINAUT

A LEVEL

4.5 Instructor Rating

100+ Courses

20+ Faculty

Industry Expert

45000+ students enrolled

UI/UX Designer, with 7+ Years Experience. Guarantee of High Quality Work.

Skills: Web Design, UI Design, UX/UI Design, Mobile Design, User Interface Design, Sketch, Photoshop, GUI, Html, Css, Grid Systems, Typography, Minimal, Template, English, Bootstrap, Responsive Web Design, Pixel Perfect, Graphic Design, Corporate, Creative, Flat, Luxury and much more.

Available for:

1. Full Time Office Work
2. Remote Work
3. Freelance
4. Contract
5. Worldwide

Reviews

Nicole Brown

UX/UI Designer

4.5 Instructor Rating

“ This is the second Photoshop course I have completed with Cristian. Worth every penny and recommend it highly. To get the most out of this course, its best to to take the Beginner to Advanced course first. The sound and video quality is of a good standard. Thank you Cristian. “