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.

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ML 009: Effective Machine Learning in Academia and Industry with Hassan Kane

ML 009: Effective Machine Learning in Academia and Industry with Hassan Kane

In this week’s episode of Adventures in Machine Learning we have Hassan Kane, data scientist lead at Entropy Labs. Hassan discusses his journey from being raised in Ivory Coast, Africa to getting his ...

13 Loka 202018min

ML 008: TensorFlow.js and YOU with Jason Mayes

ML 008: TensorFlow.js and YOU with Jason Mayes

TensorFlow is a machine learning library that allows a user to program deep learning architectures. It is normally associated with backend programming languages like Python and is written in C++, but ...

6 Loka 202046min

ML 007: Computer Vision & AI Scientist with Beril Sirmacek

ML 007: Computer Vision & AI Scientist with Beril Sirmacek

Beril Sirmacek is a data scientist and an assistant professor at Jonkoping University. She explains what computer vision is, what type of projects are done with it, and her own work regarding it. Spo...

29 Syys 202040min

ML 006: Mad Science AI with Benson Ruan

ML 006: Mad Science AI with Benson Ruan

Benson Ruan talks about his experiences as a machine learning tech lead for a fintech company in Sydney, Australia. He goes over his education in machine learning from Coursera, especially doing Andre...

22 Syys 202036min

ML 005: Transfer Learning for NLP with Daniel Svoboda

ML 005: Transfer Learning for NLP with Daniel Svoboda

One of the hottest fields right now in machine learning is natural language processing. Whether it’s getting sentiment from tweets, summarizing your documents, sarcasm detection, or predicting stock t...

15 Syys 202054min

ML 004: Automated Machine Learning ML with Jorge Torres

ML 004: Automated Machine Learning ML with Jorge Torres

Implementing deep learning algorithms require knowledge of various DL libraries, how to interface outside files or streaming data to it, along with tuning all sorts of parameters. Deep Learning also d...

11 Syys 202051min

ML 003: Your GPU Brain with Robert Plummer

ML 003: Your GPU Brain with Robert Plummer

Machine learning is a complex subject that requires knowledge in many various subjects such as linear algebra, probability, algorithms, calculus, etc. But what if you could simplify machine learning t...

10 Syys 202046min

ML 002: DeOldify Your Life with Jason Antic

ML 002: DeOldify Your Life with Jason Antic

GANS are one of the revolutionary breakthroughs in machine/deep learning as they are able to create authentic facial images. One of the latest breakthroughs has been with reconstructing actual images ...

9 Syys 20201h 5min

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