The Intersection of Success and Talent Retention in Software Development - ML 156

The Intersection of Success and Talent Retention in Software Development - ML 156

In today's episode, Michael and Ben dissect the process of building maintainable and impactful products, emphasizing the crucial balance between innovation and simplicity. They explore personal and group learning curves, the value of collaboration, and the indispensable role of peer review in creating robust solutions.


They'll also touch upon the nuanced perspectives of working at top tech companies like Google and Databricks, examining how timing and project involvement can shape a developer's skillset and career trajectory. From the importance of understanding one's career goals to the powerful impact of a company's culture on code quality, they aim to uncover the multifaceted aspects of professional growth in tech.


Join they as they delve into stories of overengineered solutions, the necessity of constructive feedback, and the collaborative efforts that define truly great products. Whether you're aspiring to join the elite 1% of developers, or simply looking to understand the dynamics of a high-functioning team, this episode is packed with insights and practical advice. So, tune in and let's explore the path to greatness together!


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

Episoder(209)

Where ML and DevOps Meet - ML 108

Where ML and DevOps Meet - ML 108

Hosts of the Adventures in DevOps podcast, Jillian Rowe and Jonathan Hall, join Ben and Michael on this week's episode crossover. They talk about the intersection of ML and DevOps. They dive into the ...

17 Mar 20231h 5min

How Does ChatGPT Work? - ML 107

How Does ChatGPT Work? - ML 107

ChatGPT is the most robust free chatbot. It can answer questions, write code, and summarize text. Today we will talk about the creation of ChatGPT, its implications for society, and how the model actu...

10 Mar 202348min

Machine Learning for Movie Scripts - ML 106

Machine Learning for Movie Scripts - ML 106

Today we look at an applied use case for ML: parsing movie scripts. Expect to learn about bringing ML to new industries, the future of Large Language Models (LLM), and automation in the movie industry...

3 Mar 202345min

ChatGPT and the Divine - ML 105

ChatGPT and the Divine - ML 105

"Any sufficiently advanced technology is indistinguishable from magic." Today, Michael and Ben talk about the broad implications of ChatGPT and similar algorithms. Expect to learn about...The differen...

23 Feb 202351min

Deep Learning for Tabular and Time Series Data - ML 104

Deep Learning for Tabular and Time Series Data - ML 104

Today we speak with a staff data scientist at Walmart who specializes in forecasting. He has built an open-source tool that allows you to leverage tabular data in PyTorch. He also has written a book o...

16 Feb 20231h 8min

Notebooks vs. IDEs With Fabian Jakobs - ML 103

Notebooks vs. IDEs With Fabian Jakobs - ML 103

How do you develop ML code? Do you use notebooks or do you use IDEs? In this episode, we get some practical advice from both Ben and our guest on leveraging software principles to write better code in...

9 Feb 202345min

How to think about Optimization - ML 102

How to think about Optimization - ML 102

In this week's episode, we meet with Micheal McCourt, the head of engineering at SigOpt. He is an industry expert on optimization algorithms, so expect to learn about constraint-active search, SigOpt'...

3 Feb 202350min

Protecting Your ML From Phishing And Hackers - ML 101

Protecting Your ML From Phishing And Hackers - ML 101

Have you ever wondered how to secure a cloud deployment? Well, today we talk to the president at a cloud security company about personal security, detecting malicious actors, startup trends, and much ...

27 Jan 202341min

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