Adventures in Machine Learning

By Charles M Wood

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Subscribers: 18
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Episodes: 209

Description

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.

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

Episode Date
Why Authenticity Beats Algorithms: The New Rules of Digital Marketing - ML 185
Apr 04, 2025
Integrating Business Needs and Technical Skills in Effective Model Serving Deployments - ML 184
Feb 13, 2025
Navigating Common Pitfalls in Data Science: Lessons from Pierpaolo Hipolito - ML 183
Jan 24, 2025
Cows, Camels, and the Human Brain - ML 182
Jan 09, 2025
A/B Testing with ML ft. Michael Berk - ML 181
Jan 02, 2025
Navigating Build vs. Buy Decisions in Emerging AI Technologies - ML 180
Dec 26, 2024
Artificial Intelligence as a Service with Peter Elger and Eóin Shanaghy - ML 179
Dec 19, 2024
Combating Burnout in Machine Learning: Strategies for Balance and Collaboration - ML 178
Dec 12, 2024
The Nature of the World and AI with Rishal Hurbans - ML 177
Dec 09, 2024
Crafting Data Solutions: Shrinking Pie and Leveraging Insights for Optimal Data Learning - ML 176
Nov 28, 2024
Challenges and Solutions in Managing Code Security for ML Developers - ML 175
Nov 21, 2024
Innovative Security Solutions for Developers - ML 174
Nov 14, 2024
Peer Review and Career Development - ML 173
Nov 07, 2024
Navigating Expertise Gaps - ML 172
Oct 31, 2024
The Influence of Gen AI on Personalized Education and Curiosity - ML 171
Oct 24, 2024
The Role of Open Source in Modern Development Practices - ML 170
Oct 17, 2024
AI-Powered Tools for Productivity with Artem Koren - ML 169
Oct 10, 2024
The Impact of Generative AI on the Advertising Industry - ML 168
Oct 03, 2024
Learning, Testing, and Mentorship: Building Autonomy and Confidence in Python Development - ML 167
Sep 26, 2024
Evaluating and Building AI Systems - ML 166
Sep 19, 2024
Demystifying AI Innovations - ML 165
Sep 12, 2024
Maintaining Backward Compatibility in Software Projects: Strategies from Industry Experts - ML 164
Aug 29, 2024
Building, Testing, and Abandoning Software - ML 163
Aug 22, 2024
AI in Education: From Micro-Courses to Rigorous Training Programs - ML 162
Aug 15, 2024
Transforming Recruitment with AI: Surveys, Sentiment, and Data-Driven Insights - ML 161
Aug 08, 2024
How AI and Deep Fakes Are Transforming Security and Customer Trust - ML 160
Jul 24, 2024
AI Deployment Simplified: Kit Ops' Role in Streamlining MLOps Practices - ML 159
Jul 18, 2024
Functional Programming Shift and Scalable Architecture Insights - ML 158
Jul 11, 2024
Mentorship and Management: Creating a Collaborative Work Environment - ML 157
Jul 04, 2024
The Intersection of Success and Talent Retention in Software Development - ML 156
Jun 27, 2024
Redefining Data Science Roles: Beyond Technical Skills and Traditional Job Descriptions - ML 155
Jun 20, 2024
Balancing Theoretical Knowledge with Hands-on Experience - ML 154
Jun 13, 2024
AI in Security: Revolutionizing Defense and Outsmarting Attackers in the Digital Era - ML 153
Jun 06, 2024
The Journey to Expertise with Fernando Lopez - ML 152
May 23, 2024
Unraveling the Complexities of Model Deployment in Dynamic Marketplaces - ML 151
May 09, 2024
The Impact of AI Tools on Software Development and Quality Assurance - ML 150
May 02, 2024
Adaptive Industry ML: Challenges, Automation, and Model Applications - ML 149
Apr 18, 2024
Harnessing Open Source Contributions in Machine Learning and Quantization - ML 148
Apr 18, 2024
Data Platform Innovation: Navigating Challenges and Building a Unified Experience - ML 147
Apr 11, 2024
The Science-Engineering Blend - ML 146
Apr 04, 2024
The Impact of Process on Successful Tech Companies - ML 145
Mar 28, 2024
Delivering Scoped Solutions: Lessons in Fixing Production System Issues - ML 144
Mar 21, 2024
MLOps 101: Scoping, Latency, Data Curation, and Continuous Model Retraining - ML 143
Mar 14, 2024
Navigating Authority and Transparency in Organizations - ML 142
Feb 22, 2024
Evolution of Dlib: Addressing Challenges in Machine Learning and Computer Vision - ML 141
Feb 08, 2024
Strategies for Improving Code Quality and Maintenance in the Python Environment - ML 140
Jan 25, 2024
Lyft's ML Infrastructure Journey - ML 139
Jan 18, 2024
From Open Source to Traditional ML with James Lamb - ML 138
Jan 04, 2024
Wars of AI and Justice: Handling Uncertainties and Ethical Quandaries - ML 137
Dec 21, 2023
Beyond Machine Learning - ML 136
Dec 07, 2023
Unraveling AI's Impact: Computer Vision, Generative Models, and Challenges in Software Development - ML 135
Nov 30, 2023
Complexity Theory - ML 134
Nov 23, 2023
How To Recession Proof Your Job - BONUS
Nov 23, 2023
Data Watchdogs - ML 133
Nov 16, 2023
Causal Analysis - ML 132
Nov 09, 2023
Data Visualization and Hugging Face - ML 131
Nov 02, 2023
Confidence as Data Scientist - ML 130
Oct 19, 2023
A Case Study: Recommendation Engines - ML 129
Oct 05, 2023
Maximizing Efficiency in ML Project Development - ML 128
Sep 21, 2023
AI that Make You Better - ML 127
Sep 14, 2023
Challenges for LLM Implementation - ML 126
Sep 07, 2023
ML in the Cannabis Industry - ML 125
Aug 24, 2023
How AI Impacts Society - ML 124
Aug 17, 2023
LLMs on Azure - ML 123
Aug 03, 2023
How to Create Team Utils - ML 122
Jul 21, 2023
How to Get Sh*t Done - ML 121
Jul 13, 2023
ML at Netflix and How to Learn Deeply - ML 120
Jun 30, 2023
How to get Promoted - ML 119
Jun 23, 2023
How does Search Work? - ML 118
Jun 15, 2023
How to Learn a New Tool - ML 117
Jun 08, 2023
The Innovation Cycle of AI - ML 116
May 25, 2023
All Things Machine Learning - ML 115
May 11, 2023
How to Transition from Academics to Industry - ML 114
May 05, 2023
How to Make your Projects Succeed - ML 113
Apr 27, 2023
Jason Weimann - Learn Video Game Development with Chuck - BONUS
Apr 21, 2023
How to Think Like a Principal Architect - ML 112
Apr 13, 2023
How Do You Stop Hating Your Job? - BONUS
Apr 13, 2023
How to Transition from Software Engineer to ML Engineer - ML 111
Apr 07, 2023
Machine Learning for Meeting Notes - ML 110
Mar 30, 2023
Model Serving at Databricks - ML 109
Mar 27, 2023
Where ML and DevOps Meet - ML 108
Mar 17, 2023
How Does ChatGPT Work? - ML 107
Mar 10, 2023
Machine Learning for Movie Scripts - ML 106
Mar 03, 2023
ChatGPT and the Divine - ML 105
Feb 23, 2023
Deep Learning for Tabular and Time Series Data - ML 104
Feb 16, 2023
Notebooks vs. IDEs With Fabian Jakobs - ML 103
Feb 09, 2023
How to think about Optimization - ML 102
Feb 03, 2023
Protecting Your ML From Phishing And Hackers - ML 101
Jan 27, 2023
The Disruptive Power of Artificial Intelligence - ML 100
Jan 19, 2023
A History Of ML And How Low Code Tooling Accelerates Solution Development - ML 099
Jan 06, 2023
Moving from Dev Notebooks to Production Code - ML 098
Dec 22, 2022
How to Edit and Contribute to Existing Code Base - ML 097
Dec 15, 2022
MLflow 2.0 And How Large-Scale Projects Are Managed In The Open Source - ML 096
Dec 01, 2022
How To Recession Proof Your Job - BONUS
Nov 24, 2022
Should you Context Switch when Writing Code? - ML 095
Nov 24, 2022
Important Questions To Ask When Scoping ML Projects - ML 094
Nov 17, 2022
How To Do Research Spikes - ML 093
Nov 10, 2022
How to Simplify Data Science with DagsHub Founders - ML 092
Oct 27, 2022
How to Test ML Code - ML 091
Oct 20, 2022
AGI, Neuron Simulators, and More with Charles Simon - ML 090
Oct 06, 2022
Complex ML Models with Data Scientist Fernando Lopez - ML 089
Sep 29, 2022
Distributed Time Series in Machine Learning - ML 088
Sep 22, 2022
Time Series Models in Machine Learning - ML 087
Sep 15, 2022
Optical Character Recognition (OCR) and Machine Learning with Ahmad Anis - ML 086
Sep 08, 2022
Innovation and AI Strategies with Award Winning Data Science Leader Vidhi Chugh - ML 085
Aug 25, 2022
Machine Learning on Mobile Devices and More with Aliaksei Mikhailiuk - ML 084
Aug 18, 2022
Leveling Up in your Data Science Career with Adam Ross Nelson - ML 083
Aug 04, 2022
Bioinformatics and Programming with Ken Youens-Clark - ML 082
Jul 29, 2022
Building AI Data Responsibly with Edouard d’Archimbaud - ML 081
Jul 21, 2022
From Golf Instructor to Software Developer: Taking Next Steps in your Career - ML 080
Jul 14, 2022
Hyperparameter Tuning for Machine Learning Models - ML 079
Jul 07, 2022
Ask Me Anything (AMA) with Host Ben Wilson - ML 078
Jun 30, 2022
Optimizers in Machine Learning, Featuring Maciej Balawejder - ML 077
Jun 23, 2022
Part 2: Exploratory Data Analysis (EDA) Next Steps - ML 076
Jun 16, 2022
Exploratory Data Analysis (EDA) in Machine Learning - ML 075
Jun 09, 2022
Apache Spark (Pt. 2): MLlib - ML 074
Jun 02, 2022
Apache Spark Integration and Platform Execution for ML - ML 073
May 26, 2022
Two Case Studies: Production ML infrastructure and Recommendation Engines - ML 072
May 18, 2022
Using AI and ML to Help Humans, Not Replace Them - ML 071
May 12, 2022
AutoML Discovery and Approach - ML 070
May 04, 2022
For Sports and Beyond: Robotics and Advanced Cognitive Computing-Based Video Processing Algorithms - ML 069
Apr 28, 2022
How to Beef Up Your Resume - ML 068
Apr 21, 2022
Training Bots, The Stock Market, and Hypotheticals - ML 067
Apr 07, 2022
How to Teach Kids Science with Kathryn Hulick - ML 066
Mar 17, 2022
Business Infrastructure in ML with Joe Reis - ML 065
Mar 09, 2022
Data Feeds and KDNuggets with Maria Zentsova - ML 064
Mar 03, 2022
Rethinking ML Monitoring Part 2 - ML 063
Feb 24, 2022
How To Do Post-Production with Abhilash Pattnaik - ML 062
Feb 18, 2022
Accurate Predictive Modeling with Maarit Widmann - ML 061
Feb 10, 2022
Rethinking ML Monitoring - ML 060
Feb 03, 2022
Solving the Real Issues with the MLflow Team - ML 059
Jan 27, 2022
Cows, Camels, and the Human Brain - ML 058
Jan 20, 2022
Business Objectives and KPIs with Michael Berk
Jan 06, 2022
Prediction Intervals - ML 056
Dec 16, 2021
3 Fundamental Pillars You Need to Succeed as an Entrepreneur - BONUS
Dec 14, 2021
How to Integrate ML and Data Science Systems to Web and Mobile Apps - ML 055
Dec 02, 2021
BONUS: How to do LARGE Volumes of HIGH Quality Work - While Spending Fewer Hours Working
Nov 25, 2021
Tools, Tricks, and Learning in Machine Learning ft. Aliaksei Mikhailiuk - ML 054
Nov 18, 2021
A/B Testing with ML ft. Michael Berk - ML 053
Nov 11, 2021
Data Paradoxes in Data Sets with Pier Paolo Ippolito - ML 052
Nov 04, 2021
Testing Your MLOps - ML 051
Oct 28, 2021
Deploying Your Machine Learning Models with FastAPI ft. Ahmad Mustafa Anis - ML 050
Oct 21, 2021
Monitoring and Evaluating Data Sets ft. Emeli Dral and Elena Samuylova - ML 049
Oct 14, 2021
The MLOps Community with Demetrios Brinkmann - ML048
Oct 07, 2021
How to Build and Organize Production ML Solutions ft. Conor Murphy - ML 047
Sep 30, 2021
Using AI to Make the LifeCycle of Software Development Easier ft. Antonio Alegria - ML 046
Sep 22, 2021
Multi-modal AI and Machine Teaching ft. Slater Victoroff - ML 045
Sep 16, 2021
AI Assisted Development ft. Sydney Lai - ML 044
Sep 02, 2021
Data + ML: What Could Go Wrong? ft. Sandeep Uttamchandani - ML 043
Aug 26, 2021
From Software Engineer to Data Engineer ft. Alexey Grigorev - ML 042
Aug 19, 2021
Writing Production Code for ML ft. Ken Youens-Clark - ML 041
Aug 12, 2021
Machine Learning for Tabular Data in Practice ft. Mark Ryan - ML 040
Aug 05, 2021
Transformers and Attention in Machine Learning ft. Ekrem Aksoy - ML 039
Jul 29, 2021
Mentorship in Machine Learning - ML 038
Jul 22, 2021
Productionized Machine Learning Engineers featuring Laszlo Sragner - ML 037
Jul 13, 2021
Data Pipelines with Metaflow featuring Ville Tuulos - ML 036
Jul 08, 2021
Machine Learning: More than Just an Algorithm - ML 035
Jul 01, 2021
How to Get Started in Machine Learning - ML 034
Jun 24, 2021
Scaling video processing with Deep Learning - ML 033
Jun 17, 2021
The 3 Essentials for Successful Job Outcomes - BONUS
Jun 04, 2021
The 3 Essentials for Successful Job Outcomes - BONUS
Jun 03, 2021
How to Get Hired at a FANG Company - BONUS
May 28, 2021
Parallelizing Model Training with Michael Galarnyk - ML 032
May 27, 2021
The Best Machine Learning Frameworks and Tensorflow Extensions with Derrick Mwiti - ML 031
May 20, 2021
Automated Machine Learning with Qingquan Song - ML 030
May 13, 2021
Becoming the Go-To Person in Your Technology Area - BONUS
May 07, 2021
Machine Learning for the Mars Rover with Annie Didier - ML 029
May 06, 2021
Tensorflow.js with Gant Laborde - ML 028
Apr 29, 2021
Don't Let These Things Keep You From Podcasting - BONUS
Apr 29, 2021
BONUS: Relationships Matter Most
Apr 23, 2021
ML 027: Staying Current in Machine Learning
Apr 22, 2021
BONUS: How Opportunities Come Your Way When You're an Influencer
Apr 16, 2021
BONUS: How Opportunities Come Your Way When You're an Influencer
Apr 15, 2021
BONUS: What is Charles Max Wood's Biggest Payoff for Being a Dev Influencer?
Apr 09, 2021
ML 026: Sweetviz with Francois Bertrand
Apr 08, 2021
BONUS: How Jason Weimann Became a Game Developer
Apr 02, 2021
ML 025: Machine Learning and Quantum Computing with Ather Fawaz
Apr 01, 2021
BONUS: Continuing Your Learning Journey by Finding Mentors as an Influencer
Mar 26, 2021
BONUS: Continuing Your Learning Journey by Finding Mentors as an Influencer
Mar 26, 2021
ML 024: Machine Learning in Action with Ben Wilson
Mar 23, 2021
ML 023: Inside Machine Learning with Edward Raff
Mar 16, 2021
BONUS: How Charles Max Wood Started Podcasting -- And You Can Too
Mar 09, 2021
BONUS: How to get Freelance Clients to Come to You
Mar 02, 2021
ML 022: Machine Learning with TensorFlow Chris Mattmann
Feb 23, 2021
ML 021: Grokking Deep Reinforcement Learning with Miguel Morales
Feb 16, 2021
BONUS: Measuring Apps and Entrepreneurship with John-Daniel Trask
Feb 05, 2021
BONUS: Measuring Apps and Entrepreneurship with John-Daniel Trask
Feb 05, 2021
ML 020: How to Make an Impact on the Development Community
Feb 02, 2021
ML 019: Artificial Intelligence as a Service with Peter Elger and Eóin Shanaghy
Jan 26, 2021
ML 018: Mastering Data Pipelines with Apache Spark with Jean-Georges Perrin
Jan 19, 2021
ML 017: The Nature of the World and AI with Rishal Hurbans
Jan 12, 2021
ML 016: Python as a Basis for Machine Learning with Ken Youens-Clark
Jan 05, 2021
BONUS: How to Crush Your Biggest Goals in 2021
Jan 01, 2021
ML 015: Extracting Value from Data with Alexey Grigorev
Dec 29, 2020
ML 014: Deep Learning with Structured Data with Mark Ryan
Dec 23, 2020
BONUS: How to do LARGE Volumes of HIGH Quality Work - While Spending Fewer Hours Working
Nov 27, 2020
ML 013: Recommender Systems with Frank Kane
Nov 17, 2020
ML 012: Machine Learning for Mere Mortals with Nick Chase
Nov 03, 2020
ML 011: History of AI in the UK with Laurence Moroney
Oct 27, 2020
ML 010: Brains, Guitars, and JavaScript with Milecia McGregor
Oct 20, 2020
ML 009: Effective Machine Learning in Academia and Industry with Hassan Kane
Oct 13, 2020
ML 008: TensorFlow.js and YOU with Jason Mayes
Oct 06, 2020
ML 007: Computer Vision & AI Scientist with Beril Sirmacek
Sep 29, 2020
ML 006: Mad Science AI with Benson Ruan
Sep 22, 2020
ML 005: Transfer Learning for NLP with Daniel Svoboda
Sep 15, 2020
ML 004: Automated Machine Learning ML with Jorge Torres
Sep 11, 2020
ML 003: Your GPU Brain with Robert Plummer
Sep 10, 2020
ML 002: DeOldify Your Life with Jason Antic
Sep 09, 2020
ML 001: The Adventures in Machine Learning First Steps
Sep 08, 2020