By the end of this course, you will have the skills you need to confidently build your own models using Python.

Applied Unsupervised Learning with Python

3 Day Course with 1 Hour Webex Follow up

Course Description

Starting with the basics, Applied Unsupervised Learning with Python explains various techniques that you can apply to your data using the powerful Python libraries so that your unlabeled data reveals solutions to all your business questions

Overview

Unsupervised learning is a useful and practical solution in situations where labeled data is not available.

Applied Unsupervised Learning with Python guides you on the best practices for using unsupervised learning techniques in tandem with Python libraries and extracting meaningful information from unstructured data. The course begins by explaining how basic clustering works to find similar data points in a set. Once you are well versed with the k-means algorithm and how it operates, you’ll learn what dimensionality reduction is and where to apply it. As you progress, you’ll learn various neural network techniques and how they can improve your model. While studying the applications of unsupervised learning, you will also understand how to mine topics that are trending on Twitter and Facebook and build a news recommendation engine for users. You will complete the course by challenging yourself through various interesting activities such as performing a Market Basket Analysis and identifying relationships between different merchandises.

By the end of this course, you will have the skills you need to confidently build your own models using Python.

After completing this course, you will be able to:

• Understand the basics and importance of clustering

• Build k-means, hierarchical, and DBSCAN clustering algorithms from scratch with built-in packages

• Explore dimensionality reduction and its applications

• Use scikit-learn (sklearn) to implement and analyse principal component analysis (PCA)on the Iris dataset

• Employ Keras to build autoencoder models for the CIFAR-10 dataset

• Apply the Apriori algorithm with machine learning extensions (Mlxtend) to study transaction data

Scope

This course is beneficial for individuals having prior programming knowledge Python. Basic knowledge of mathematical concepts, including exponents, square roots, means, and medians is expected.

Target Audience

This course is designed for developers, data scientists, and machine learning enthusiasts who are interested in unsupervised learning. Some familiarity with Python programming along with basic knowledge of mathematical concepts including exponents, square roots, means, and medians will be beneficial.

Course Outline

Lesson 1: Introduction to Clustering

• Introduction

• Unsupervised Learning versus Supervised Learning

• Clustering

• Introduction to k-means Clustering

Lesson 2: Hierarchical Clustering

• Introduction

• Clustering Refresher

• The Organization of Hierarchy

• Introduction to Hierarchical Clustering

• Linkage

• Agglomerative versus Divisive Clustering

• k-means versus Hierarchical Clustering

Lesson 3: Neighborhood Approaches and DBSCAN

• Introduction

• Introduction to DBSCAN

• DBSCAN Versus k-means and Hierarchical Clustering

Lesson 4: Dimension Reduction and PCA

• Introduction

• Overview of Dimensionality Reduction Techniques

• PCA

Lesson 5: Autoencoders

• Introduction

• Fundamentals of Artificial Neural Networks

• Autoencoders

Lesson 6: t-Distributed Stochastic Neighbor Embedding (t-SNE)

• Introduction

• Stochastic Neighbor Embedding (SNE)

• Interpreting t-SNE Plots

Lesson 7: Topic Modeling

• Introduction

• Cleaning Text Data

• Latent Dirichlet Allocation

• Non-Negative Matrix Factorization

Lesson 8: Market Basket Analysis

• Introduction

• Market Basket Analysis

• Characteristics of Transaction Data

• Apriori Algorithm

• Association Rules

Lesson 9: Hotspot Analysis

• Introduction

• Kernel Density Estimation

• Hotspot Analysis

Acumen Envision run Technical IT courses that are engaging, creative and with content that sticks.

Super Creative

We don't believe in traditional & acceptable We do believe in Creative, Engaging & Sticky. People are not the same, the way they learn is not the same so a program has to engage all mindsets. We use a complex mix of engaging tools combined first class classroom delivery, and continuous measurement to ensure we produce true mindset and behavioural change.

Skilled Instructors

Without our highly skilled training team all of the pre-course consultancy and technology customisation would just not work. The wealth of experience and real world scenarios that they bring to each classroom module enhances the discussion, engagement and overall delivery. So, whether your people are attending a 1-1 Group or Public Technology program they will receive top level classroom tuition as part of their overall learning experience.

Acumen Envision the Transformation Specialists

Specialist Technical IT Training, Sticky Effective Disruptive, We Deliver First Class Results.

Data Science Training for Data Scientists, Data Analysts, Software Developers or Anyone working in a role or wanting to work with large data sets.

Our Data Science courses cover Data Visualization, Python, Jupyter, R, AI, Machine Learning, Data Wrangling, Excel VBA, Access VBA, Scala, Spark, Power BI, Tableau and much more.

Courses run for Data People by Data Specialists.

What’s Included:

• The latest Data Science course content

• Trainers who enjoy Data Science, delivering courses and talking about real word examples.

• Detailed course work book to take away

• Our Extras Pack for post course learning

• Certificate of completion

• Unlimited Refreshments

Why our content sticks.

• We take time to know our participants with pre course evaluation

• We don’t run large class sizes

• Our courses are delivered by subject matter experts who make the content engaging

• We like Hands on, so you can absorb the theory with practice

• We provide a 1-hour WebEx follow up to see how you are getting on to give any additional advice

Want something different?

• Can I have a course on my own. Yes, you can we can provide a 1:1 course for you either on-site or in centre.

• 1-1 or Group Training for your business, no problem.

We can customise content, combine courses or develop a program around your team or specific need.

• Need us to look at something specific, in a black hole with Excel / Access or need to migrate large amounts of data then please contact us to discuss in more detail. Our training are experts in their own field and spend 40% of their time providing on / off site consultancy.

What happens after I book?

• You will get a booking confirmation once you have placed your order.

• If you are booking a course over a weekend don’t worry one of our team will contact you via email on Monday to double check the details with you and check to see if you would like to book an optional lunch.

• We will send you the link to down load all of the tools and software needed for your course.

• 7 Days before your course date we send a reminder

• The morning of the course the course lecturer will greet you in reception if 1:1 course or in the training room if a group course.

• If you need help with anything don’t panic simply call or email us and we will assist.

Our list of Data Science Courses

• Applied Data Science with Python & Jupyter

• Applied Data Visualization with R and ggplot2

• Artificial Intelligence with Big Data

• Big Data Analysing with Python

• Big Data Processing with Apache Spark

• Data Science for Marketing Analytics

• Data Science Projects with Python

• Data Virtualisation with Python

• Data Wrangling with Python

• Excel – Introduction

• Excel – Advanced

• Excel for Data Analysis with Power Pivot

• Excel – Forecasting Data

• Excel – Sparkline and Mapping Data

• Excel – Visualising Data with Charts

• Excel - Dashboards

• Excel VBA Programming

• Access VBA

• VBA Programming

• Microsoft Power BI Data Analysis Professional

• Microsoft Power BI Data Analysis Practitioner

• Scala and Spark with Big Data Analytics

• Python Programming Introduction

• Python Advanced Programming

• Python API Development

• Python Microservices Development

• Machine Learning with Python

• Applied Unsupervised Learning with Python Libraries

• SQL for Data Analytics

• SQL Query Fundamentals

• Tableau Introduction

• Tableau Advanced

Refund Policy

We will provide a refund for all cancellations received 14 days prior to the event.

We accept name changes up to 3 days before the event at no additional cost , if you are unable to attend.

If for any reason we have to cancel the event we will offer you the option to move onto the next available date, attend an alternative course or we will provide a full refund.

Please note that we are not liable for any travel or accommodation costs relating to your course booking.

We always try to help and be as fair as possible, so please contact us at your earliest convenience if you are unable to attend a course you have booked, so we can look at the options available for you.