Machine Learning is growing in leaps and bounds both in capability and adoption. Listen to our experts discuss the ideas and fundamentals needed to succeed as a Machine Learning Engineer.
Hyperparameter Tuning for Machine Learning Models - ML 079
When developing ML models, defining and selecting the model architecture will be fundamental to ensure the best possible outcomes. Parameters that define the model architecture are referred to as hyperparameters and the process of searching for the ideal model architecture is referred to as hyperparameter tuning. Today on the show, Ben and Michael discuss hyperparameter tuning and how to implement this into your ML modeling. In this episode… Why do we tune? Optimizing the models Hyperparameter tuning Steps for tuning Data splits Linear based models How do you know when you know enough? Basic rules of thumb Buffer in time for spikes Grid searching and automation Sponsors Top End Devs Coaching | Top End Devs
Ask Me Anything (AMA) with Host Ben Wilson - ML 078
Enjoy this engaging AMA conversation with Michael Berk asking Ben Wilson various questions related to industry, strategy, and approaches in data science and ML engineering.In this episode… Why should people trust you? What will you lose by hearing about other people’s failures vs. personally failing to learn? How do you view the current industry? Do you think data scientists and ML engineers are overpaid? What are 3 things important to ROI? How do you set the tone for culture? Sponsors Top End Devs Coaching | Top End Devs LinksMachine Learning Engineering in Action
Optimizers in Machine Learning, Featuring Maciej Balawejder - ML 077
Ben and Michael interview Maciej Balawejder, a mechanical engineering student passionate about AI, ML, and robotics. As an active contributor on Medium.com, Maciej has already made significant contributions to the AI and ML communities. On the show, they discuss Maciej’s recent article about optimizers in Machine Learning, plus their personal philosophies and approaches to deep learning.Sponsors Top End Devs Coaching | Top End Devs Links Maciej Balawejder - Medium Optimizers in Machine Learning
Part 2: Exploratory Data Analysis (EDA) Next Steps - ML 076
After ensuring your data has surpassed the hyper parameter tuning phase, what is the next step in your EDA protocol? Today on the show, Ben and Michael continue the discussion on EDA methodology within Machine Learning and discuss linear regression with OLS, decision trees, and common visualization tools for data scientists. In this episode... Linear regression with OLS Accuracy metrics Decision trees Shapley values Common visualization tools Sponsors Top End Devs Coaching | Top End Devs
Exploratory Data Analysis (EDA) in Machine Learning - ML 075
EDA is primarily used in machine learning to see what data can reveal beyond the formal modeling or hypothesis testing task and provides a better understanding of data set variables and the relationships between them. It can also help determine if the statistical techniques you are considering for data analysis are appropriate. Today on the show, Ben and Michael discuss how to use EDA in machine learning models. In this episode... What is EDA? Tips and Tricks and steps for EDA How to approach downsampling Understanding feature sets relative to your labels Optimizing models Motivating yourself to get into the data Tools for EDA A few scenarios for discussion What is the most detrimental EDA mistake for ML Sponsors Top End Devs Coaching | Top End Devs
Apache Spark (Pt. 2): MLlib - ML 074
MLlib is Apache Spark's scalable machine learning library. Today, Ben and Michael discuss the ease of use, performance, algorithms, and utilities included in this library and how to execute the best ML workflow with MLlib. In this episode... Why stick with Spark libraries vs. a single node operation? What algorithms are not in Spark Lib? What is the min. package set to use for supervised learning? Modeling and validation Down-sampling your data MLlib vs. scikit-learn Resources Sponsors Top End Devs Coaching | Top End Devs Links MLlib | Apache Spark What is PySpark? | Domino Data Science Dictionary UCI Machine Learning Repository
Apache Spark Integration and Platform Execution for ML - ML 073
Apache Spark is a lightning-fast unified analytics engine for large-scale data processing and machine learning. In this episode, Ben and Michael unpack Spark by ping-ponging questions and answers, supplemented by various examples applicable to machine learning workflows. In this Episode… How does Spark work? What makes Apache Spark effective? Dot repartition in Spark Parallel processing systems What is an aggregation in Spark sequel? Analytics with Spark What is MPP? Testing for production Spark algorithms Sponsors Top End Devs Coaching | Top End Devs Sponsored By: Coaching | Top End Devs: Do you want to level up your career? or go freelance? or start a podcast or youtube channel? Let Charles Max Wood Help You Achieve Your Dreams Top End Devs: Learn to Become a Top 5% Developer. Join our community of ambitious and engaged programmers to learn how.
Two Case Studies: Production ML infrastructure and Recommendation Engines - ML 072
Ben and Michael walk through two different cases studies relative to production ML infrastructure and recommendation engines. The first is about a free on-line tutoring service for underserved communities called “Learn to Be”, and the second centers around the online course provider “Coursera”. Ben and Michael set up the case studies with fundamental problem statements, followed by their various approaches to executing the objectives to achieve the desired process outcomes. Sponsors Top End Devs Coaching | Top End Devs Sponsored By: Coaching | Top End Devs: Do you want to level up your career? or go freelance? or start a podcast or youtube channel? Let Charles Max Wood Help You Achieve Your Dreams Top End Devs: Learn to Become a Top 5% Developer. Join our community of ambitious and engaged programmers to learn how.
Using AI and ML to Help Humans, Not Replace Them - ML 071
Ben interviews Michael Griffiths, Director of Data Science at ASAPP, a company leveraging AI and ML to augment and automate human work, improve operational efficiencies and customer experiences, and ultimately empower people to be their best. Michael shares specific examples of how this can be done for human agent productivity within contact centers. They also discuss fully human controlled vs automated systems, delivering value with AI and ML, and the future of AI driven technology. In this Episode… How do you deliver value with AI and ML? Fully human controlled vs. fully automated systems ML software engineering vs traditional software Using static training data models and data validation Communicating process improvements and failures What is the future of ASAPP and AI driven technology? Sponsors Top End Devs Coaching | Top End Devs Links How a Level System can Help Forecast AI Costs - KDnuggets AI Research - ASAPP ASAPP Special Guest: Michael Griffiths.Sponsored By: Coaching | Top End Devs: Do you want to level up your career? or go freelance? or start a podcast or youtube channel? Let Charles Max Wood Help You Achieve Your Dreams Top End Devs: Learn to Become a Top 5% Developer. Join our community of ambitious and engaged programmers to learn how.
AutoML Discovery and Approach - ML 070
AutoML (automated machine learning) has become a hot topic over the past few years. Abid Ali Awan joins the show to share his approach to AutoML, when and how to utilize it compared to classic approaches. Ben and Abid also discuss open-source vs. proprietary platforms. What is AutoML? Automated machine learning provides methods and processes to make machine learning available for non-machine learning experts, to improve efficiency of machine learning and to accelerate research on machine learning. 2 levels of implementation: Blackbox AutoML can do one, or all of the things for feature selection with a statistical outset and self optimizing outcome. Whitebox AutoML exposes the code to explain how it behaves and allows you to produce predictions as to the influencing variables. Leveraging open-source toolkits vs. proprietary “The output is the model, the input is the data, and you can use that model to predict anything according to your business problem.” - Abid Ali Awan Sponsors Top End Devs Coaching | Top End Devs Links H2O.ai Special Guest: Abid Ali Awan .Sponsored By: Coaching | Top End Devs: Do you want to level up your career? or go freelance? or start a podcast or youtube channel? Let Charles Max Wood Help You Achieve Your Dreams Top End Devs: Learn to Become a Top 5% Developer. Join our community of ambitious and engaged programmers to learn how.
For Sports and Beyond: Robotics and Advanced Cognitive Computing-Based Video Processing Algorithms - ML 069
Video is considered the most complicated data to process and the volumes of video production are growing from day to day. Ben and Michael talk with Oleg and Anastasiya about how to leverage robotics and advanced cognitive computing-based video processing algorithms to automate the most routine parts of editing and post-production. Specifically, they discuss American sports such as the NFL, NBA, and NHL, and how to use AI to automate sports highlight reels can automate content post-processing video analytics to save time and streamline employee workflows. This is an exciting video you won’t want to miss! Sponsors Top End Devs Coaching | Top End Devs Special Guest: Anastasiya Vishnevskaya.Sponsored By: Coaching | Top End Devs: Do you want to level up your career? or go freelance? or start a podcast or youtube channel? Let Charles Max Wood Help You Achieve Your Dreams Top End Devs: Learn to Become a Top 5% Developer. Join our community of ambitious and engaged programmers to learn how.
How to Beef Up Your Resume - ML 068
Michael and Ben talk about how to pick extra projects to build up your resume and become recognized as more of an expert. They discuss the specific ways to contribute within the community and who to interact with to strengthen your resume if you're new. Sponsors Top End Devs Coaching | Top End Devs Sponsored By: Coaching | Top End Devs: Do you want to level up your career? or go freelance? or start a podcast or youtube channel? Let Charles Max Wood Help You Achieve Your Dreams Top End Devs: Learn to Become a Top 5% Developer. Join our community of ambitious and engaged programmers to learn how.
Training Bots, The Stock Market, and Hypotheticals - ML 067
Machine learning is getting bigger by the second, so it’s good to know how to leverage it. In this episode, Michael asks Ben hypothetical questions around how to effectively deploy machine learning in multiple fields, including the stock market. In This Episode 1) How to get started in the stock market without having gobs of hedge fund money 2) The ONE thing you NEED to know before even starting a project in this space (or you’re wasting your time AND money) 3) The BEST way to leverage open source software and have a competitive advantage Sponsors Top End Devs Coaching | Top End Devs Sponsored By: Coaching | Top End Devs: Do you want to level up your career? or go freelance? or start a podcast or youtube channel? Let Charles Max Wood Help You Achieve Your Dreams Top End Devs: Learn to Become a Top 5% Developer. Join our community of ambitious and engaged programmers to learn how.
How to Teach Kids Science with Kathryn Hulick - ML 066
What happens when you teach ML and data science to kids? You learn a whole lot, too. In this episode, Ben and Michael sit down with Kathryn, a prolific writer and author who simplifies advanced concepts for kids to foster their passion for science. “I just love how curious kids are. I really connect with the questions they ask and how curious they are, so that’s why I love writing for them.” - Kathryn Hulick In This Episode 1) What you NEED to remember when trying to teach complicated topics to kids 2) The BIGGEST misconception around AI that kids need to understand 3) How we can approach ML and data science to learn better (and how kids already do this!) Sponsors Top End Devs Coaching | Top End Devs Special Guest: Kathryn Hulick.Sponsored By: Coaching | Top End Devs: Do you want to level up your career? or go freelance? or start a podcast or youtube channel? Let Charles Max Wood Help You Achieve Your Dreams Top End Devs: Learn to Become a Top 5% Developer. Join our community of ambitious and engaged programmers to learn how.
Business Infrastructure in ML with Joe Reis - ML 065
Even an amazing algorithm can’t fix communication problems. In this episode, Ben and Michael sit down with Joe Reis, a data scientist and ML developer who’s passionate about helping people level up their communication and build solid business infrastructure. “I feel like the infrastructure piece is getting better. Once you get past the technical layer, it’s about basic things like communication, no matter how much money is thrown into it.” - Joe Reis In This Episode 1) SUPER exciting trends for data science for the first time in 10+ years 2) Why you NEED to have a marketing-focused approach in the ML space nowadays 3) The BIGGEST things you should consider when hiring and scaling to keep you business infrastructure intact Sponsors Top End Devs Coaching | Top End Devs Links Joe Reis ( JoeReis ) Sponsored By: Coaching | Top End Devs: Do you want to level up your career? or go freelance? or start a podcast or youtube channel? Let Charles Max Wood Help You Achieve Your Dreams Top End Devs: Learn to Become a Top 5% Developer. Join our community of ambitious and engaged programmers to learn how.