Simply Artificial Intelligence Review

Simply Artificial Intelligence Review

Table of Contents

Ever wondered what Artificial Intelligence (AI) could do for you if only you could understand it without needing a PhD? It’s a lot like asking whether a manual exists that can transform us from mere spectators to active participants in this revolution. Enter “Simply Artificial Intelligence Hardcover – Big Book, 7 March 2023,” a title that sounds daunting until you crack open its cover and realize it’s more like having a light-hearted coffee chat with a tech-savvy friend. Let’s get into the finer details, shall we?

Simply Artificial Intelligence     Hardcover – Big Book, 7 March 2023

Click to view the Simply Artificial Intelligence     Hardcover – Big Book, 7 March 2023.

Simply Introduced: What Sets It Apart?

The joy of “Simply Artificial Intelligence” lies in its accessibility. AI is often shrouded in complexity, akin to those algebra textbooks we used to hide from. This book, however, manages to cut through the jargon with the finesse of a warm knife through butter. It’s as if the authors knew that explanations about machine learning needed a pinch of humor and a dash of relatability.

Gunning for Graspability

What truly grabbed us was its intent to simplify without oversimplifying. It’s easy to imagine AI as some dark, mysterious force plotting our demise. But this book reassures us that AI can indeed be both practical and beneficial—think of it as demystifying a magician’s tricks without ruining the magic.

Who Can Use This Book?

We loved that it’s not just for tech geeks or Silicon Valley aficionados. From students with stars in their eyes to professionals who’ve read one too many intimidating articles on AI, this book invites everyone to the table. It’s much like David Sedaris inviting you into his world, making you feel right at home as he recounts life stories that are both extraordinary and humdrum.

A Table For Your Thoughts

To bring some structure to our admiration, let’s break down what “Simply Artificial Intelligence” offers:

Feature Description Why It Matters
Accessibility Written in layman’s terms Easier understanding for non-experts
Humor Light-hearted, funny anecdotes Makes learning enjoyable
Real-world Examples Practical applications demonstrated Connects theory with practice
Expert Insights Contributions from industry leaders Credibility and advanced knowledge

The book manages to be both enlightening and fun, like discovering your favorite comedian is also a closet philosopher.

Simply Artificial Intelligence Hardcover – Big Book, 7 March 2023

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Unfolding the Layers: Content Breakdown

When you unbox this hardcover gem, you’re greeted with content that’s organized elegantly. It doesn’t overcrowd your mental space but rather walks you through foundational concepts before daring to venture into more complex territories. It’s the perfect blend of nurture and challenge—much like Sedaris’ way of casually throwing curveballs in his narrative that make you pause and ponder.

The Basics: Foundations of AI

Before we get carried away with complex algorithms or dystopian futures, the book pulls us back to ground zero. The basics are laid out simply, covering the history of AI and its evolution. It’s much like understanding why David Sedaris preferred listening to music instead of practicing social interactions—context adds richness.

Cracking the Code: Machine Learning and More

A significant portion pays homage to machine learning, the workhorse behind most AI applications today. The book delves into neural networks, algorithms, and data science. Think of these sections as discovering how Sedaris constructs each essay—structured yet spontaneous.

Ethics: Can We Trust AI?

Here’s where it feels more like a Davids Sedaris essay, part contemplative, part philosophical. The book asks us to confront the ethical dimensions of AI. Can we create something more intelligent than us without it turning against us? It’s a question that lingers like an unresolved plotline in a short story.

Future Perspectives: What Lies Ahead?

It includes a speculative yet pragmatic discussion about the future of AI. Much like Sedaris would ponder the peculiarities of everyday life, the book encourages us to think, question, and imagine what AI could mean for us in years to come.

Find your new Simply Artificial Intelligence     Hardcover – Big Book, 7 March 2023 on this page.

Why It Works: The Hidden Craft

Creating a book that holds the reader’s attention from start to finish is no small feat, especially when the subject is as intricate as AI. But much like Sedaris’ unique storytelling, the creators of “Simply Artificial Intelligence” have woven a narrative that is captivating and informative.

Humor: The Secret Ingredient

One would think that discussing AI demands a straight-laced, academic approach. Yet, this book employs humor to keep us engaged. The light-hearted tone translates complicated subjects into digestible chunks, kind of like Sedaris turning mundane events into laugh-out-loud moments.

Relatable Analogies: Simplifying the Complex

Ever tried understanding AI through the lens of cooking recipes or carpentry? This book walks us through machine learning as if we’re mastering a new culinary dish. Sedaris would likely approve of these quirky analogies, given his penchant for drawing vivid parallels between disparate worlds.

Expert Opinions: Anchoring the Flight of Imagination

The book doesn’t shy away from calling in the experts. Industry leaders provide their insights, anchoring the whimsical flights of imagination in expert opinion, much like Sedaris might balance humor with poignant truths.

Real-World Impact: Beyond The Pages

Simply reading about AI is one thing. But how does this book translate its wisdom into actionable takeaways for us?

Learning and Application: Two Sides of the Same Coin

The book doesn’t just leave us awestruck with theory; it arms us with practical knowledge. Whether you’re a student, a professional, or a curious mind, the book offers tools to implement in real life, making the complex subject of AI notably approachable.

Broadening Career Horizons

For those of us looking to pivot careers or expand our skill set, the book is a goldmine. It’s as if Sedaris decided to write a guide on navigating workplace quirks—humorous, insightful, but most importantly, practical. Various chapters offer hands-on advice, making the intimidating task of entering the field of AI much more attainable.

Implications for Everyday Life

AI is not just for grand enterprises but for everyday life too. Whether we’re talking about personal assistants like Siri and Alexa, or more complex decisions like data-driven healthcare, this book connects high-tech with our daily grind, much like Sedaris finds profound meaning in everyday absurdities.

Simply Artificial Intelligence     Hardcover – Big Book, 7 March 2023

A Word on the Authors

Having a credible set of authors is like finding a reliable narrator in one of Sedaris’ stories. The creators of “Simply Artificial Intelligence” come with impeccable credentials, making the book not just a light read but an authoritative one as well. Their style, however, leans away from dry academia, embracing a more personable narrative.

Backgrounds That Inspire Confidence

These authors have been knee-deep in the world of AI for years. Their combined experiences range from research to hands-on development. Imagine if Sedaris collaborated with fellow humorists; the result would be both rich and entertaining. Such is the impact of expert knowledge filtered through a lens of accessibility.

Dedication to Education

One can’t help but notice the authors’ commitment to making complex subjects accessible. It’s as if their mission aligns with Sedaris’ goal of making his whimsical observations relatable and engaging. They want us to not just read but to learn, absorb, and apply.

Their Approach: Holding Our Interest

Using a conversational style, the authors effectively draw us into the world of AI without turning us off with overly technical jargon. It’s like Sedaris’ knack for transforming a seemingly trivial event into a narrative worth remembering.

Turning Pages: What Keeps Us Hooked?

When it comes to learning about AI, monotony is the arch-nemesis. What makes “Simply Artificial Intelligence” so engaging that we flip through pages with the eagerness of a toddler unwrapping a birthday gift?

Compelling Narration

Blending informative content with relatable anecdotes, the authors have created a narrative that’s both enlightening and entertaining. It feels akin to Sedaris introducing us to his quirky family gatherings—each story as unpredictable and engaging as the last.

Visual Aids and Diagrams

Diagrams and visual aids are sprinkled throughout the book, providing mental breaks and helping us visualize complex systems. Think of these as the pictorial anecdotes Sedaris inserts to illustrate a particularly odd family member or strange life event.

Summaries and Takeaways

Each chapter wraps up with summaries and actionable takeaways. This structure ensures that we don’t just read but retain and apply the knowledge. It’s a lot like Sedaris summarizing his humorous yet insightful observations in a punchline that leaves us both amused and contemplative.

Simply Artificial Intelligence     Hardcover – Big Book, 7 March 2023

Reader Feedback: Echoes from the Page

We aren’t the only ones captivated by this book. Here’s what other readers have to say, creating a mosaic of diverse opinions that add depth to our impression.

Praise for Simplicity

Many readers appreciate how the book manages to simplify an overwhelmingly complex topic. They liken it to Sedaris’ writing style, which takes convoluted life experiences and distills them into relatable, often hilarious anecdotes.

Applicability in Varied Fields

Professionals from varied fields commend the book for its practicality. Whether you’re in healthcare, finance, or education, readers find actionable insights that span industries, much like Sedaris’ observational humor resonates across different walks of life.

Constructive Criticism

Some readers have noted that while the book focuses heavily on accessibility, it occasionally sacrifices depth. They compare it to yearning for more intricate family backstories in a Sedaris essay. However, these criticisms are minor hiccups in an otherwise well-rounded narrative.

Conclusion: A Must-Have on Your Bookshelf

“Simply Artificial Intelligence Hardcover – Big Book, 7 March 2023” is not just a book; it’s an experience. Much like reading David Sedaris, it leaves us both entertained and wiser. It’s a tool, a guide, and a companion for anyone venturing into the labyrinthine world of AI.

If you’re looking to demystify AI and want to do so in a manner that’s both educational and enjoyable, this book belongs on your bookshelf. As Sedaris might say, it’s the kind of book that keeps you sane amid the growing complexities of modern life. So grab a copy, sit back, and let “Simply Artificial Intelligence” take you on a journey that’s both enlightening and fun.

Get your own Simply Artificial Intelligence     Hardcover – Big Book, 7 March 2023 today.

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University Student Essentials
University Student Essentials

About Me

With 25 years of experience in healthcare IT implementation, Emmanuel began his career at the University of Pittsburgh Medical Center, working as an assistant manager for a billing system implementation. Over the years, he has explored various aspects of the healthcare IT domain, successfully implementing several laboratory information systems and electronic medical record (EMR) systems, such as Cerner Millennium and Epic EMR.

In 2005, Emmanuel shifted his focus to public health, working on bio-surveillance implementation for the Centers for Disease Control and Prevention (CDC). He contributed to the BioSense Data Provisioning Project and performed extensive analysis of HL7 messages in hospitals and healthcare facilities. Additionally, Emmanuel requirements analysis for the CDC BioSense Analysis, Visualization and Reporting (AVR) project and played a key role in publishing the Situational Awareness updates to the BioSense System Requirements Specification (SRS).

Over the past 11 years, Emmanuel has worked in the Middle East, implementing the Epic EMR system at Cleveland Clinic Abu Dhabi. As a multidisciplinary team member, he has taken on various roles, including SCRUM Master, Project Manager, Integration Engineer, and Platform Engineer. Concurrently working as an adjunct university faculty member, teaching graduate-level courses in Systems Life Cycle and undergraduate courses in Health Information Systems

From a technological standpoint, Emmanuel has designed, installed, and implemented complete hospital integration systems using Rhapsody Integration Engine, MS SQL Server, and Public Health Information Networks Messaging System (PHINMS). He has also developed over 10,000 interfaces some of which coded in Java and JavaScript.

In 2019, Emmanuel expanded his skill set and entered the field of digital marketing, quickly becoming a proficient Digital Marketing Strategist. He has since helped numerous clients develop robust digital marketing strategies for their businesses. His expertise encompasses Social Media Marketing, On-page and Off-page SEO, Google Ads, and Google Analytics. Additionally, he and a team have managed clients’ website development projects, ensuring that each site is optimized for SEO, further enhancing their online presence and performance.

Alongside their digital marketing expertise, Emmanuel has delved into the world of Affiliate Marketing, where Emmanuel and his team successfully managed and executed campaigns for a variety of clients. By identifying the right products and services to promote, Emmanuel and his team helped clients generate passive income streams and increase their overall revenue.

Their approach to Affiliate Marketing involves creating valuable content that educates and engages the target audience, while strategically incorporating affiliate links. Emmanuel and his team have experience working with multiple affiliate networks and platforms, ensuring optimal tracking and reporting of performance metrics. By staying up to date with the latest trends and best practices, Emmanuel and his team have been able to optimize affiliate campaigns for maximum results, fostering long-term partnerships and sustainable growth for their clients.

As an accomplished professional, Emmanuel holds dual Bachelor of Arts degrees in Linguistics and English, a Master of Science in Health Information Systems from the University of Pittsburgh, and a Ph.D. in Information Systems from Nova Southeastern University.

My Teaching History

Professor Bazile is a dedicated technology instructor and Adjunct Faculty professor, who began his teaching career in April 2000 at the Business Career Institute in Las Vegas, Nevada.

In 2001, he expanded his expertise by training nurses in the use of Electronic Medical Records (EMR) systems. His experience in both technology and healthcare led to his appointment as an Adjunct Faculty professor at the University of Phoenix in May 2008, where he has taught several graduate-level information technology and healthcare information systems courses.

Dr. Bazile has also developed an HL7 course, which he has taught at various healthcare facilities, drawing from his own book, “HL7: Introductory and Advanced Concepts,” currently available on Amazon. With a passion for teaching and a commitment to ensuring students get the most out of each course he teaches, Dr. Bazile is a valuable asset to both his students and the institutions he serves.

My Teaching Philosophy

My teaching philosophy as an Information Systems professor in healthcare is built on the concept that education should equip students to be confident and capable problem solvers who are prepared to traverse the complicated and ever-changing landscape of Healthcare IT.

In order to accomplish this, I prioritize the creation of a dynamic and engaging learning environment that encourages students to engage with course material and with one another. This involves employing a range of teaching approaches, such as lectures, seminars, and hands-on activities, to ensure that students learn in the manner that best matches their learning style.

I believe the reason we have Information Systems as a discipline is to allow students to apply technology to solve real world problems. If that is the case, both undergraduate and graduate students have to be challenged to incorporate their core academic courses with their matriculated subjects. As such, it is important that students enter their Junior and Senior years with a strong command of the core courses such as Programming, databases, networks, hardware and software, as they serve as the foundation upon which real-world solutions will be built.

I also believe in the importance of incorporating real-world examples and case studies into my courses, as this helps to connect abstract concepts to practical applications. Additionally, I encourage students to apply what they are learning to their own personal and professional goals, as this helps to make the material more meaningful and relevant to their lives.

I strive to foster a positive and supportive learning environment where all students feel comfortable asking questions and participating in class discussions. I believe that this is key to fostering a sense of community and ensuring that all students have the opportunity to succeed.

I have also taught online courses. I have found in an asynchronous learning environment it can be difficult to apply the Peer Teaching or Experiential Learning Pedagogical Approaches. However, I have found the Discovery Learning approach to works quite well. Along with a boost to students’ self-confidence, Discovery Learning in an online environment allows students to synthesize information, expand on existing concepts on their own, while experiencing a positive outcome through trial and error.

Ultimately, my mission as an educator, and a Healthcare IT Information Systems professor is to provide students with the knowledge, skills, and confidence they need to thrive and succeed in their careers and to be technological leaders. By creating a positive and supportive learning environment, incorporating real-world examples and case studies, and encouraging students to apply what they are learning to their own objectives; my hope is to inspire and empower all students to achieve their full potential.

Population Size:

A total of 310 responses were originally received. Any response containing missing data due to unclicked radio buttons or unchecked checkboxes were first reviewed, and, if justified, were omitted from analysis. For surveys with missing data, a total of 18 responses were removed. In order to address any issues with response-set, the data was downloaded into Microsoft Access and queries ran to identify responses that contained the same values for each question. A total of 16 responses were found to be qualified for removal. Another 18 were identified as outliers and removed leaving a total of 258 responses for the study analysis.

In order to assess multivariate outliers, the Mahalanobis distances were calculated and plotted against their corresponding Chi-Square distribution percentiles (Schmidt & Hunter, 2003). The resulting scatterplot is similar to a univariate normal Q-Q plot, where deviations from a straight line show evidence of non-normality. The data showed indications of moderate deviations from multivariate normality, as indicated by the concavity of the data points. There were no additional multivariate outliers or missing values in the data after the removal of 52 responses.

Descriptive Statistics

Frequencies and percentages were conducted for the demographics indicators, while means and standard deviations were calculated for the continuous indicators. For gender, there were 151 females (59%) and 107 males (41%) in the sample. For ethnicity, most participants were Caucasian (119, 46%), followed by African American (56, 22%). The two most populous education levels were Bachelor’s (90, 35%) and Master’s (62, 22%). The biggest proportion of the sample by age group was the 35-44 age group (101, 39%) followed by the 45-54 age group (59, 23%).

Analysis:

Confirmatory Factor Analysis and Composite Reliability

A CFA was conducted along with a reliability analysis to assess construct validity. Examination of modification indices and factor loadings indicated that CSE1, CSE5, CSE7, PC5, ATE1, ATE6, ATE8, PP5, and PP6 were all causing significant problems with the model parameters. The results of the last iteration of the CFA performed in R showed significantly improved fit, although still poor overall (χ2(545) = 2125.61, p < .001, CFI = 0.82, TLI = 0.81, RMSEA = 0.11). The high degrees of freedom indicate that a very large number of parameters are being estimated in this model.

Composite Reliability

For the full model, each construct had excellent reliability. The ATE latent construct had a composite reliability value of 0.89. The ORC construct had a composite reliability value of 0.94. The CSE latent construct had a composite reliability value of 0.85 and PC had a composite reliability value of 0.95. For PP and RES, the composite reliability scores were 0.80 and 0.96 respectively. These values indicate that the loadings for each construct were all directionally similar, and that the items in each construct show a high degree of consistency.

Cronbach’s Alpha

Cronbach’s alpha values were calculated for the items in each construct. The alphas for PC (α = 0.90), AXY (α = 0.94), and RES (α = 0.94) indicated excellent reliability. The alphas for CSE (α = 0.80), ATE (α = 0.88), and PP (α = 0.83) all showed good reliability. These values confirm the results of the composite reliability tests, and reiterate the high degree of reliability within each latent construct.

Partial Least Squares – Structural Equation Modeling

A partial least squares- structural equation modeling (PLS-SEM) was conducted to determine how well the data fit the proposed model, and discern whether significant relationships existed between the independent and dependent constructs. The full model showed AVE values of 0.53 for ATE, 0.69 for AXY, 0.44 for CSE, .72 for PC, .35 for PP, and 0.81 for RES. The high values for AXY, PC, and RES indicate that the amount of variance accounted for in the manifest variables is sufficiently high. The values for ATE, CSE, and PP indicate that some of the variance in the manifest variables is left unexplained.

Structural Model

Once the measurement model had been tested for model specification, the structural model was tested to determine if ATE, AXY, CSE, PC, and PP had a significant effect on RES. A path weighted model was calculated using 10,000 bootstrap samples in R. The results showed a pseudo R-squared value of 0.78. This indicates that approximately 78% of the variance in RES is explainable by the collective effects of CSE, PC, ATE, PP, and AXY.

Further examination of the effects indicated that AXY had a highly significant effect on RES (= 0.87, < .001). This indicates that a standard deviation increase in AXY increases the expected value of RES by 0.87 standard deviations. CSE did not have a significant effect on RES (= 0.02, = .423). Additionally, CSE (= 0.02, = .423), PC (= 0.05, = .334), ATE (= 0.00, = .983), and PP (= 0.03, = .407) did not have significant effects on RES. Table 11 outlines the results of the path estimates.

Correlation Analyses

Both Pearson and Spearman correlations were calculated on the composite scores. The results of the Pearson correlations indicated that CSE was significantly correlated AXY (= 0.22, < .001) and RES (= 0.21, < .001). The results also indicated that PC was significantly correlated with ATE (= -0.79, < .001), AXY (= 0.18, < .001), and RES (= 0.20, < .001). ATE was significantly correlated with AXY (= -0.19, < .001) and RES (= -0.19, < .001). AXY was significantly correlated with RES (= 0.85, < .001).

ANCOVA Analyses

An analysis of covariance (ANCOVA) was conducted to determine if a significant relationship existed between the AXY, PP, CSE, PC, ATE scores and RES controlling for Gender, Age, Ethnicity, Education, and Specialty. The overall model was found to be significant (F(63,194) = 53.39, < .001), with an R2 value of .95, indicating that 95% of the variance in RES was explained by the collective effect of the independent variables and covariates.

Since the overall model was found to be significant, the model’s covariates were assessed. The AXY (F(10,194) = 262.20, < .001), ATE (F(7,194) = 2.20, = .036), Years computers (F(1,194) = 5.71, = .018), and PC (F(12,194) = 2.00, = .026) scores were found to be significant, indicating that a significant amount of variance in RES is explained by AXY, ATE, and PC.

A path diagram depicting the results of the structural model.

Results

This research investigated Computer Self-Efficacy (CSE), Perceived Complexity (PC), Attitudes toward EMR Systems (ATE), Peer Pressure (PP), and Anxiety (AXY) to determine whether these constructs as individuals, or as a group, or coupled together with some other factors could significantly explain resistance to EMR systems. Quantitative examination of self-reported survey results was performed to understand the strength and significance of the relationships, while these relationships were investigated to test the strength of model fit.

the regression paths of the structural model were examined to test the hypotheses. Significance was determined using an alpha level of .05. The model had an overall R2 value of 0.78. This indicates that approximately 78% of the variability in RES can be accounted for by CSE, PC, ATE, PP, and AXY. Since the overall model was significant, the individual coefficients can be interpreted. Some of the hypotheses were supported by the results of this study, and some were rejected. The construction of a data model of the relationships in this study could not meet thresholds that would be evidence of a good fit of the relationships identified in the study.

The fifth hypotheses tested the influence of AXY on resistance to EMR systems. AXY was expressed to be significantly related to resistance (r=.87, p<.001). This finding supports the hypothesis that anxiety with the EMR system will lead to medical care professionals rejecting use of the system. Unlike the findings of the first four hypotheses, the findings of the current study support previous research. Angst and Agarwal (2009) indicated that AXY is a factor which is significantly related to the problem of EMR system resistance. Based on the empirical findings of previous research, the present research and conceptual propositions and conclusions in previously written scholarly articles, there is a great deal of support for the finding that AXY is significantly influenced by EMR resistance.

The findings of this research do not support all findings by previous researchers, and there are multiple relationships which had been established as being significant that were identified as being insignificant in the current research. Generally, because of the inconsistency of previous findings and the current study there may be elements related to the sample examined or other contextual factors which may contribute to the inconsistency that exists. Ultimately, it is suggested that there be further research done on the problem of resistance to EMR system use.

Ultimately the findings support a new take on the problem of EMR system resistance that may contribute to the ways in which scholars investigate the problem of EMR resistance in general. This may also help with the way practitioners approach EMR systems, and articulate value of the systems to medical professionals investing record-keeping systems in the workplace.