A view of 2021 from mid-year

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A view of 2021 mid-year, is part looking back and part looking to the future. Where have I been? Where will I be? Could I write something intensely personal. Yes. However, that is not along the themes I usually write about.

The year 2021 has become more normal starting during a pandemic and will likely end after the pandemic has lifted. Does that change and impact define my 2021? No. The discussion of reflection and predication for a year should not be defined by what did not happen, but what has and is likely to occur.

In reflection, I have…


What is a Chatbot?

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Websites have developed over time from simple pages with links to now containing embedded apps and dynamic storage, video and audio.

The chatbot has become a standard to include on websites to allow users on a page to connect with the page owner for artificial conversations with high availability.

The chatbot is based logic, natural language processing, and artificial intelligence. When checking a utility bill online, there is a small icon in a bubble for “live chat”, which is a chatbot for customer service. The chatbot allows the user to retrieve account information in a native way, place billing inquiries…


Same, Similar, or Different?

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Analytics come in different types based on what information is needed. Time-based information rely on analysis from data that includes time. There are four types of analysis: descriptive, diagnostic, predictive, and prescriptive. When focusing on what will happen, there are two types, predictive and prescriptive. Often these are confused, but are results that tell two different stories from data.

Predictive Analysis encompasses a variety of statistical techniques from data mining, predictive modelling, and machine learning that analyze current and historical facts to make predictions about future or otherwise unknown events.

Prescriptive Analysis uses statistical models and machine learning algorithms to…


June 2021

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Our second newsletter for the Inside Dataology Publication is here. Expect a monthly newsletter with information about the publication and updates.

The publication covers topics in data from inside. Topics including career advice, personal experience, guides and tutorials are sections of the publication. Interested in writing for Inside Dataology?

More about Submissions Here.

Top three articles from May 2021

  1. Easiest Way to Know Your Dataset
  2. Talk Data to Me — What’s the Hype Around Analyzing It?
  3. From public sector projects to private sector tech — an unintentional journey


Data Visualization for Text

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Data visualization is an important piece of data analytics and data science. Representing information and knowledge by a graphic or illustration brings new context and wider audience appeal. Statistics and numbers are easy when they result from work done by one person, for teams, and teams with individuals from different backgrounds, representation and communication of findings is critical. There are many types of visuals for data standard in many apps and tooling. There are bar charts, line charts, pie charts, and scatter plots for example. …


A story of healthcare data in five visualizations for analysis.

Data representation is important to communicate data and results to stakeholders. There are different types of visualizations available in most applications for analysis and analytics. Using programming to analyze data, there are more options that unique to the definition of graphical representation by the coder. For applications such as Excel, Power BI, and Tableau, there are at least 24 available from menus.

Visualizations

Card is a single number, usually a count of an item or type.

Bar is a presentation of the association of two values showing amount per item.

Line is similar to bar but shows variation or change.

Scatter


The difference between List, Array, and DataFrame.

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Data is used within programming to store facts that are manipulated into a result. The result could be an action or a function to generate information. The facts to support transformation come in many forms. Data can be numeric, character, boolean, and others. The way the data is organized in Python can vary. The three most common forms are List, Array, and DataFrame.

Lists

A List is a data type in python. This data type is constructed of multiple values in a 1D structure of any data type. There are cases of Nested Lists and these are multi-dimensional. Lists are a…


Eight Skills Available for Learning about Artificial Intelligence or Machine Learning

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Alexa is an AI from Amazon that is voice activated and can respond in natural language. It can perform information retrieval tasks, shopping notifications, and integrate to become a smart home device. Part of Alexa is access to Amazon Skills. Amazon Skills has access to many podcasts and apps for educational goals.

Over the years, many consumers have asked “how many Alexa skills are there?”, to which Amazon responded and publicly stated that there are over 100,000 unique Alexa skills globally. Feb 5, 2021 from PolicyAdvice.net

Skills for AI/ML

Searching for AI/ML skills yields a small piece of available skills mostly organized as…


May 2021

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Hello, the first Newsletter for the Inside Dataology Publication is finished. Expect a monthly newsletter with information about the publication and updates.

The publication covers topics in data from inside. Topics including career advice, personal experience, guides and tutorials are sections of the publication. Interested in writing for Inside Dataology?

More about Submissions Here.

Top three articles from April 2021

  1. Tools for Machine Learning and Artificial Intelligence in Analytics
  2. Using Data Mining in Digital Marketing Implementation Methods and Performance Metrics
  3. Easiest Way to Know Your Dataset


AI Bias, What and How?

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When creating an AI algorithm, natural language processing for a chatbot or phone system, a solution to recognize images via clustering data from a camera or sensor, there is a probability of a correct result. The gage is a statistical analysis representing the fit of solution to the expected or known results from a training set. Creating solutions that make sense and provide utility is a challenge to Artificial Intelligence and Machine Learning in real world settings. …

Sarah Mason

Sarah Mason is a health analytics consultant at Sarah Mason Consulting LLC. www.sarahmasonconsulting.com

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