Machine Learning with Python
Description
What you’ll learn
Speak fluently about machine learning
Have an understanding of what is involved with using machine learning in Python
Understand what machine learning is and can do
Course content
Expand all 49 lectures05:17:46
–Course Introduction
02:02
Introduction
Preview
02:02
–Machine Learning Concepts
14:00
Introduction
00:38
Supervised and Unsupervised Learning
08:34
Semi-Supervised Learning
04:25
Summary
00:23
–First ML Application
01:10:56
Introduction
01:49
Installing the Environment
02:54
Hello World
07:34
Installing Aaconda and Deep Learning Libraries
Preview
10:18
Email Spam Checker – Part 1
07:09
Email Spam Checker – Part 2
13:39
Email Spam Checker Results
08:35
Iris 70/30 – Part 1
08:56
Iris 70/30 – Part 2
09:18
Summary
00:44
–Data Analysis
33:44
Introduction
00:32
Data Analysis – Example 1
12:57
Data Analysis – Example 2
10:47
Data Visualization
08:44
Summary
00:44
–Linear Algebra
01:03:54
Introduction
00:59
Parametric Algorithms
Preview
06:52
Linear Algebra
09:35
Linear Regression Calculation – Part 1
12:42
Linear Regression Calculation – Part 2
05:03
Regression on Larger Dataset – Part 1
10:18
Regression on Larger Dataset – Part 2
07:38
Regression on Larger Dataset – Part 3
10:09
Summary
00:38
–Natural Language Processing
01:09:02
Introduction
01:03
Natural Language Processing – Part 1
08:57
Natural Language Processing – Part 2
03:57
Tokenizing Content
Preview
11:21
Processing Unique Words
13:11
Summarizing Headlines – Part 1
09:18
Summarizing Headlines – Part 2
11:54
Summarizing Headlines – Part 3
08:31
Summary
00:50
–Clustering
01:03:54
Introduction
01:03
Cluster Introduction
Preview
08:31
EM and M Clustering
06:18
Clustering Code Walkthrough
09:07
Clustering Iris Data – Part 1
08:57
Clustering Iris Data – Part 2
08:43
Clustering Iris Data – Part 3
08:15
Dendrogram Graphs
10:01
Summary
Preview
00:59
Course Summary
02:00
–Bonus Material
00:13
Bonus Lecture: Course Discounts
00:13
Requirements
Experience programming.
Experience with Python will be helpful.
Description
If you’re plugged into the tech industry, you’ll know that two things have been making consistent waves in many areas over the past few years; machine learning and Python. What happens when you combine the new gold standard programming language with the most significant tech development in areas such as financial trading, online search, digital marketing and even data and personal security (among others)? Great things, that’s what. This course will show you what’s what, and get you started on becoming a machine learning guru.
Learn the New Future of Programming
Understand what machine learning is and what it can do
Discover how Python utilises machine learning
Build machine learning processing from the ground up
Delve into complex logic and data structures
Increase Your Python Expertise
If you have a desire to learn machine learning concepts and have some previous programming or Python experience, this course is perfect for you. If you’re more of a beginner than an intermediate, don’t worry; each module starts with theory to explain upcoming concepts. Once you’re comfortable, you’ll put your knowledge into practice with a code walk through.
The goal of this course is to build procedural machine learning from the ground up. Writing processing from scratch allows students to gain a more in-depth insight into data processing, and as each machine learning app is created, explanations and comments are provided to help students understand why things are being done in certain ways. Each code walk through also shows the building process in real time.
The course begins with an introduction to machine learning concepts, after which you’ll build your first machine learning application. Following that, we look at data analysis, linear algebra, natural language processing and clustering, all within the context of Python. At the end of the course, you’ll be issued with a certificate of completion and will have gained a full introduction into the world of machine learning with Python.
What is Machine Learning?
Machine learning is a method of data analysis that essentially allows computers to ‘learn’ on their own without being explicitly programmed. For example, when you stop scrolling through Facebook to read a friend or a page’s post, algorithms automatically work to make sure you’ll see more content from those sources earlier in your news feed in future.
Who this course is for:
Desire to learn machine learning concepts
Wants to build machine learning processing from the ground up
Ok with complex logic and data structures
Internet Marketing Course
Digital marketing is the component of marketing that utilizes internet and online based digital technologies such as desktop computers,
mobile phones and other digital media and platforms to promote products and services. Its development during the 1990s and 2000s,
changed the way brands and businesses use technology for marketing. As digital platforms became increasingly incorporated into marketing plans and everyday life,
and as people increasingly use digital devices instead of visiting physical shops, digital marketing campaigns have become prevalent,
employing combinations of search engine optimization (SEO), search engine marketing (SEM), content marketing, influencer marketing, content automation,
campaign marketing, data-driven marketing, e-commerce marketing, social media marketing, social media optimization, e-mail direct marketing, display advertising,
e–books, and optical disks and games have become commonplace. Digital marketing extends to non-Internet channels that provide digital media, such as television,
mobile phones (SMS and MMS), callback, and on-hold mobile ring tones. The extension to non-Internet channels differentiates digital marketing from online marketing.
tristian –
This is Digital Download service, the course is available at Coursecui.com and Email download delivery.