Adventures in Machine Learning

Charles Simon, BSEE, MSCs is a nationally recognized entrepreneur and software developer who has many years of computer experience in industry including pioneering work in artificial intelligence (AI).  Mr. Simon's technical experience includes the creation of two unique AI systems along with software for successful neurological test equipment combining AI development with biomedical nerve signal testing that gives him the singular insight.  Today on the show, Charles, Michael, and Ben explore the riveting future of AGI and other illuminating technology concepts.  This is an exciting episode you won’t want to miss!

In this episode…

• Charles Simon’s extensive background
• Classical algorithms vs manual design
• Knowledge and power generated in our brains
• AI and ML concepts and learning patterns
• Graph based approaches and deep learning
• “Terminator” and AGI
• Future AI and open source simulator
• Leveraging technology to solve problems 

Sponsors

• Top End Devs
• Coaching | Top End Devs

Links

• The Team
• LinkedIn: Charles Simon

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Fernando Lopez joins the show today to share his ML insights with a video interview recruiting platform for candidate hiring.  Michael and Ben also deep dive into various related ML models and AI topics.

In this episode…

• Core software engineering skills
• Practice data algorithms and structures 
• Working towards production-grade ML
• Data engineering and data structures
• Using state-of-the-art models 
• Applying labels to data
• The AI revolution 
• Eliminating bias and unweighted data set
• Unconscious and conscious exercises
• Complex models with structure

Sponsors

• Top End Devs
• Coaching | Top End Devs

Links

• How to Package and Distribute Machine Learning Models with MLFlow - KDnuggets
• Twitter: @ferneutronn

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Today the panel discusses high level distributed time series models, using a hot dog stand company as the case study to anchor the understanding with these models.

In this episode…

• Understanding use case
• ML flow models and events
• KPI forecasts
• Metadata outputs
• Prediction intervals for hotdog data
• Automated time series forecasts
• Libraries required for optimization
• Practical tips managing the data and
• Setting up the data for consumption
• Managing black swan events

Sponsors

• Top End Devs
• Coaching | Top End Devs

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Today on the show, the panel discusses time series models, practical tips and tricks, and shares stories and examples of various models and the processes for optimal application in your ML workflows.

In this episode…

• Ben’s time series model for sales forecasting
• The flat line model
• Examples using time series models
• Understanding your data
• Lag functions and moving averages 
• Signal processing in models
• Manually adding change points
• Deep learning in time series models 
  
  

Sponsors

• Top End Devs
• Coaching | Top End Devs

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Optical character recognition, or OCR for short, is used to describe algorithms and techniques (both electronic and mechanical) to convert images of text to machine-encoded text.  Today on the show, Ahmad Anis shares how he applies Machine Learning to OCR for small hardware applications, for example, blurring a face in a video in real time or on a stream to safeguard privacy using AI.  The panel also discusses various strategies related to learning and soft skills needed for success within the industry.

In this episode…

• Optical character recognition (OCR) defined
• Multiprocessing vs. multithreading 
• I/O bound tasks vs. CPU tasks
• How to handle a retry in Python
• Strategies for employing on small hardware 
• Template matching and preprocessing 
• Gray scaling integrations
• How to learn and get started within the industry
• Reducing the scope and industry soft skills 

Sponsors

• Top End Devs
• Coaching | Top End Devs

Links

• LinkedIn: Ahmad Anis
• Twitter: @AhmadMustafaAn1

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Award winning data evangelist, AI strategist, and innovation leader Vidhi Chugh joins the show today to share her perspective on various topics, including data quality, AI innovation strategies, responsible AI, model intelligence, and much more!

In this episode…

• The importance of innovation
• Glorified failure projects 
• Responsible AI
• Data driven companies and quality scores
• Tools for autogenerated business insights
• Model intelligence 
• Unspoken assumptions
• Understanding the larger picture

Sponsors

• Top End Devs
• Coaching | Top End Devs

Links

• Benefits Of Becoming A Data-First Enterprise - KDnuggets
• Top 3 Challenges for Data & Analytics Leaders - KDnuggets
• Democratizing Data in Large Enterprises
• LinkedIn: Vidhi Chugh

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Enjoy this intellectually stimulating conversation with Michael Berk and guest on the show, Aliaksei Mikhailiuk, ML/AI engineer at Snapchat as they discuss everything AI computer graphics to techniques on striking the efficiency-accuracy trade-off for deep neural networks on constrained devices.
In this episode…

• From academics to machine learning
• Machine learning on mobile devices
• Cloud computing
• Applying AI to computer graphics
• Being multi-disciplinary 
• User experience and latency
• Model complexity issues

Sponsors

• Top End Devs
• Coaching | Top End Devs

Links

• Deep Video Inpainting. Removing unwanted objects from videos… | by Aliaksei Mikhailiuk | Towards Data Science
• On the edge — deploying deep learning applications on mobile | by Aliaksei Mikhailiuk | Jul, 2022 | Towards Data Science
• Seven Questions to Ask before Introducing AI into Your Project | by Aliaksei Mikhailiuk | Towards Data Science
• Aliaksei Mikhailiuk
• Aliaksei Mikhailiuk – Medium
• LinkedIn: Aliaksei Mikhailiuk
• Twitter: @mikhailiuka

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Adam Ross Nelson helps current and aspiring data professionals enter and level up in the field by uncovering and showcasing their existing data-related talents.  Today on the show, Michael interviews Adam to share his various strategies and approaches on how to become a data scientist or make advanced changes in the data science career path.

In this episode…

• The “distributed portfolio approach” vs. professional portfolio 
• Leveraging each platforms strengths 
• Creating a personal brand
• Find others to network and connect with
• Create a Rosetta stone in your programming language
• Pandas-profiling to contribute to the community
• Working with a career coach
• Asking the right interview questions

Sponsors

• Top End Devs
• Coaching | Top End Devs

Links

• Data Science Projects Accepting Community Contributions | by Adam Ross Nelson | May, 2022 | Towards Data Science
• Adam Ross Nelson
• LinkedIn: Adam Ross Nelson
• Twitter: @AdamRossNelson

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Michael Berk interviews Ken Youens-Clark today to discuss various topics including bioinformatics and programming, plus his career progressions including jazz drumming, technical writing, programming, academia, writing books, and solutions engineering.  

In this episode…

• Writing tests and type annotations
• Project development lifecycle
• Grading programmers with pass / fail
• Soft skills within the industry
• Bioinformatics and computer science
• Prototyping and improving efficiencies

Connect with Ken Youens-Clark via email and LinkedIn

Sponsors

• Top End Devs
• Coaching | Top End Devs

Links

• Mastering Python for Bioinformatics
• Command-Line Rust
• GitHub - kyclark/command-line-rust
• LinkedIn: Ken Youens-Clark
• GitHub: kyclark

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Data excellence is the foundation of better AI.  Today on the show, Michael Berk interviews Edouard d’Archimbaud, co-founder of Kili Technology, a Training Data Platform that turns raw, unstructured data to high-quality training data, at scale.  Enjoy this engaging conversation about building AI responsibly on a foundation of good data. 
In this episode…

1. What is cautious AI and trustworthy AI?
2. Defining clean data vs. diverse data
3. Image classification
4. How was Kili founded?
5. How does the labeler and model work together?
6. Algorithms and model structures  
7. Scaling with large data sets

Sponsors

• Top End Devs
• Coaching | Top End Devs

Links

• Kili Technology
• Blog posts
• LinkedIn: Edouard d'Archimbaud

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Privacy & Opt-Out: https://redcircle.com/privacy

Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.