What Is the EU’s Artificial Intelligence Act and What Will It Change? by Sara Tähtinen via @TDataScience

Explaining the proposed AI regulations in the EU.

This is really important to understand even if you do not create or use them yourself as the chances are that something you do use them even if it is via your bank.

Decision Trees vs Random Forests, Explained by Natassha Selvaraj via @kdnuggets

A simple, non-math-heavy explanation of two popular tree-based machine learning models.

I liked this which was nice and easy to understand if you aren't great at maths and formulas.

Primary Supervised Learning Algorithms Used in Machine Learning by Kevin Vu via @kdnuggets

In this tutorial, they are going to list some of the most common algorithms that are used in supervised learning along with a practical tutorial on such algorithms.

This is really useful and worth a bookmark or printout.

“Semantic-free” is the future of Business Intelligence by Andrew Taft via @FlexItAnalytics

 Metrics and universal semantic layers enable semantic-free BI.

I found this very interesting and worth reading so you can think about the future.

Using Machine Learning to Help Protect the Great Barrier Reef in Partnership with Australia’s CSIRO by Megha Malpani and Ard Oerlemans via @TensorFlow

In spite of the costs, machine learning has been successfully used in a variety of conservation projects around the world. Here's an inside look at how the Great Barrier Reef Foundation leveraged the latest technologies to survey, monitor and map reefs at scale.

This is a great example of something good to come out of machine learning which generally gets so much bad press about it taking over jobs.

WEBINAR: Assessing Readiness for Machine Learning in IoT - 19 May 2022

 

Webinar Series Register Today Date: Thursday, May 19, 2022 Time: 10:00 am PDT/ 1:00 pm ET Duration: 60 minutes Presented by: SUMMARY Machine learning is an incredibly powerful technology. The explosion and continued acceleration of machine learning products and ideas puts technology professionals in a position to figure out how machine learning is going to impact their business and their products. The lingering question, “Is my company ready for machine learning?” Is something that requires careful analysis.  In this IoT Central webinar, you will learn: Machine learning fundamentals How ML differs from standard software and product development How you can assess whether your company is ready to get started The secret sauce to a successful machine learning project Navigating the technologies and approaches for the journey By the end of the webinar, you will have the knowledge to know where you are in the journey, understand whether machine learning is a good strategic move for your business, and be inspired to take the next steps forward. Whether your company is already using machine learning and wants to accelerate or if you are brand new to it, the information shared in this webinar will provide you with a plan and greater confidence to proceed.   Speaker: Ben Jacques Software Engineering Manager  SpinDance  Register Today

WEBINAR: Assessing Readiness for Machine Learning in IoT - 19 May 2022

 

Webinar Series Assessing Readiness for Machine Learning in IoT Register Today Date: Thursday, May 19, 2022 Time: 10:00 am PDT/ 1:00 pm ET Duration: 60 minutes Presented by: SUMMARY Machine learning is an incredibly powerful technology. The explosion and continued acceleration of machine learning products and ideas puts technology professionals in a position to figure out how machine learning is going to impact their business and their products. The lingering question, “Is my company ready for machine learning?” Is something that requires careful analysis.  In this IoT Central webinar, you will learn: Machine learning fundamentals How ML differs from standard software and product development How you can assess whether your company is ready to get started The secret sauce to a successful machine learning project Navigating the technologies and approaches for the journey By the end of the webinar, you will have the knowledge to know where you are in the journey, understand whether machine learning is a good strategic move for your business, and be inspired to take the next steps forward. Whether your company is already using machine learning and wants to accelerate or if you are brand new to it, the information shared in this webinar will provide you with a plan and greater confidence to proceed. Speaker: Ben Jacques, Software Engineering Manager, SpinDance  Register Today

Boost Performance of Text Classification tasks with Easy Data Augmentation by Satyam Kumar via @TDataScience

Text data augmentation for NLP tasks.

Interesting thoughts and definitely something to try.

How to Run 30 Machine Learning Models with a Few Lines of Code by Ismael Araujo via @TDataScience

Learn how to run multiple machine learning models using lazy predict.

This is really neat and so you need to bookmark or add it to something like Evernote so you can use this in your Python code.

WEBINAR:Building data pipelines that drive highly predictive, resilient models - 19 April 2022

 

Building data pipelines that drive highly predictive, resilient models What: A free online webinar exclusively for IT Pros When: Tuesday, April 19th, 12:00 PM EDT Where: From the convenience of your personal computer  Register Now Predictive performance and resiliency are equally important requirements for model operationalization. Users would rather have resilient models with “good” performance than models that show high predictivity at training and testing, but underperform when deployed, and require frequent tuning. Of the multiple impactors of performance and resilience, it is well known that training data has an outsize impact on predictivity, and data drift is a major influencer of resilience. In this webinar Anindya Datta, Founder and CEO of Mobilewalla, will discuss two strategies to improve accuracy and resiliency of models: Enriching first party data to create effective training data sets that possess adequate breadth, depth and scale Using the concept of data stability to reduce the impact of data drift and produce resilient models from scratch In discussing these strategies, we will address the following questions: Why machine learning models often underperform in production How data enrichment can improve model performance The concept of data stability, and how it can be used proactively Discuss how feature transformation and selection is so critical to model resilience

101 DATA SCIENCE with Cheat Sheets (ML, DL, Scraping, Python, R, SQL, Maths & Statistics) by Anushka Bajpai via @Medium

Data Science is an ever-growing field, there are numerous tools & techniques to remember. It is not possible for anyone to remember all the functions, operations and formulas of each concept. That’s why we have cheat sheets and summaries. They help us access the most commonly needed reminders for making our Data Science journey fast and easy.

This is really like a one-stop-shop for cheatsheets - definitely worth a bookmark, a printout, adding to Evernote or whatever is your choice for preserving something important.

WEBINAR: Classify Non-Human Voice Audio for Automation and Embedded Machine Learning - 12 August 2022

Workshop Series Classify Non-Human Voice Audio for Automation and Embedded ML Register Today Date: Tuesday, April 12, 2022 Time: 9:00 am PDT | 4 pm UTC | 7:00 pm EET Duration: 23 minutes In this IoT Central MicroSession, learn how to create a non-human voice audio classification system with Edge Impulse to identify when a faucet is leaking. This demo can also be adapted for industrial use cases, such as identifying machine failures with grinding sounds, or even for wildlife conservation purposes, to recognize the vocalizations of various endangered species in the wild. Instructor: Jenny Plunkett, Senior Developer Relations Engineer, Edge Impulse Optional Hardware: Mobile Phone Preperation: Free sign-up at https://studio.edgeimpulse.com/signup Register Today

Top 3 Free Resources to Learn Linear Algebra for Machine Learning by Natassha Selvaraj via @kdnuggets

This article will solely focus on learning linear algebra, as it forms the backbone of machine learning model implementation.

I suggest you do something to get your mathematics up to a great standard - I actually did a course on Coursera which again was free.

An Easy Guide to Choose the Right Machine Learning Algorithm by Yogita Kinha via @kdnuggets

There's no free lunch in machine learning. So, determining which algorithm to use depends on many factors from the type of problem at hand to the type of output you are looking for. This guide offers several considerations to review when exploring the right ML approach for your dataset.

This is really useful and in many ways, I wish it had been available years ago. Worth a bookmark.

WEBINAR - Microsession - How to Classify Motions Using Embedded ML and Accelerometers - 15 March 2022

 

Workshop Series How to Classify Motions Using  Embedded ML and Accelerometers Register Today Date: Tuesday, March 15, 2022 Time: 9:00 am PDT | 4 pm UTC | 6:00 pm EET Duration: 15 minutes In this IoT Central MicroSession, learn how to classify three-axis motion signatures with machine learning using Edge Impulse. You will navigate through the full MLOps pipeline from the data collection to the live inferencing passing by the digital signal processing features extraction and the neural network training. Instructor: Louis Moreau, Senior DevRel Engineer, Edge Impulse Optional Hardware: Sensor or smartphone with 3-axis accelerometer Preparation: Free sign-up at https://studio.edgeimpulse.com/signup Register Today

10 Regression Metrics Data Scientist Must Know (Python-Sklearn Code Included) by T Z J Y via @Medium

A great article that definitely needs to be added to your notes and kept for reference. I've printed it and put it in a folder and also added it to my Evernote so I can refer back to it when needed.

5 Jupyter Extensions to Improve your Productivity by @CornelliusYW by @TDataScience

These packages would extend the Jupyter Notebook Functionality.

These are definitely worth a test and assessment as I think they will make your life much easier in Jupyter.

All Machine Learning Algorithms You Should Know in 2022 by Terence Shin via @TDataScience

Intuitive explanations of the most popular machine learning models.

This is really useful and definitely worth a read in case there is something new you haven't seen or come across yet. I particularly like that they are grouped into the type of algorithm.

WEBINAR: Factory 5.0: ML-Powered Manufacturing Workshop - 18 November 2021

 

Workshop Series Click Here to Register Title: Factory 5.0: ML-Powered Manufacturing Workshop  Date: Thursday, November 18, 2021 Time: 8:00 am PST/ 4:00 pm UTC Duration: 120 minutes   SUMMARY This live two-hour workshop is hosted by Arduino PRO’s enterprise-class hardware and Edge Impulse, the world’s leading embedded ML platform for the enterprise. This workshop caters to professionals who are seeking to learn how to build AI-powered solutions for manufacturing processes. Paying participants will receive an official Edge Impulse certificate signed by the CEO, which will be mailed to every registrant who attends and completes the workshop.  Overview: Smart Industry is here and it's helping almost every industry do a lot more with a lot less. From logistics, manufacturing, automotive, retail, oil & gas, pharma, to medicine, companies can start the process of digitization step by step just using the visual data they have accumulated via cameras, advanced MCUs, and machine learning. Such AI-powered systems can provide more than just accurate results but can help humans get more done, eliminating mundane and repetitive tasks.  Sample use cases that can be applied to most other industries: Learn how to apply computer vision to determine counterfeit  Scan for defective goods during the packaging processes Use machine vision to find objects or humans in restricted areas Use computer vision for quality control of pests in agriculture Apply computer vision for maintaining security perimeters Deploy AI to control the goods on the shelves of the supermarket Hardware: Core Board: Arduino Portenta H7 Lite Vision Shield: Arduino Portenta Vision Shield - Ethernet Instructor: Louis Moreau, User Success Engineer, Edge Impulse Guest: Andrea Richetta, Head of Arduino PRO Customer Success   Click Here to Register

How Netflix uses A/B tests to inform decisions and continuously innovate by/via @NetflixEng

Here are the first four parts in the multi-part series from the Netflix blog on how they use A/B tests to innovate their products.

#1 Decision Making at Netflix

#2 What is an A/B Test?

#3 Interpreting A/B test results: false positives and statistical significance

#4 Interpreting A/B test results: false negatives and power

I strongly recommend that you follow the Netflix blog as you will find a lot of really great educational information that are not just dry lessons but are based on real-life knowledge and experience.