This week, Jon Krohn and A.I. industry veteran Ben Taylor discuss the driving factors that push CEOs to prioritize A.I. over other technologies.

Additional materials: www.superdatascience.com/594

The Super Data Science Podcast: Machine Learning | AI | Success

SDS 594: Why CEOs Care About A.I. More than Other Technologies

6.20 peeks at the MLB standings (0:37), checks some Fantasy topline numbers (4:42), sets some second half over/unders (7:20), and reviews Dylan Cease (23:04).

Episode6.20 - Someone We Have Derided

Tune in as Joe Reis and Matt Housley, co-founders of Ternary Data and co-authors of the book “Fundamentals of Data Engineering” join Jon Krohn to discuss major undercurrents across the data engineering lifecycle, and their top tools and techniques.

In this episode you will learn:
• What is data engineering? [3:55]
• Why Joe and Matt identify as “recovering data scientists” [6:12]
• What kinds of people tend to become data scientists vs. data engineers [10:38]?
• Key components of Joe and Matt’s book [26:31]
• Major undercurrents across the data engineering lifecycle [28:26]
• The most under-utilized tool in a data engineer's toolbox [34:39]
• How there are tradeoffs in any data pipeline latency considerations, but faster is typically the default assumption [38:55]
• Joe and Matt’s favorite data engineering tools and techniques [43:39]

Additional materials: www.superdatascience.com/595

SDS 595: Data Engineering 101

Ben Taylor returns for a third Five-Minute Friday episode! This week, he looks ahead and digs into what we can expect from the A.I. platforms of the future.

Additional materials: www.superdatascience.com/596

SDS 596: The A.I. Platforms of the Future

Dr. Miles Brundage, Head of Policy Research at OpenAI, joins Jon Krohn this week to discuss AI model production, policy, safety, and alignment. Tune in to hear him speak on GPT-3, DALL-E, Codex, and CLIP as well.

In this episode you will learn:
• Miles’ role as Head of Policy Research at OpenAI [4:35]
• OpenAI's DALL-E model [7:20]
• OpenAI's natural language model GPT-3 [30:43]
• OpenAI's automated software-writing model Codex [36:57]
• OpenAI’s CLIP model [44:01]
• What sets AI policy, AI safety, and AI alignment apart from each other [1:07:03]
• How A.I. will likely augment more professions than it displaces them [1:12:06]

Additional materials: www.superdatascience.com/597

SDS 597: A.I. Policy at OpenAI

6.21 bats around some MLB trade deadline topics (0:38), checks some Fantasy topline numbers (2:37), kicks around some EPL (5:06), wanders through Natural Language Processing for interpreting transaction logs (8:12), and reviews Jack Flaherty (23:29).

Episode 6.21 - They Don’t Play in the Same Ballpark

Ben Taylor makes a fourth appearance on Five-Minute Friday to discuss the best ways to introduce STEM to children. Tune in to hear the many ways in which he thinks STEM education will evolve in the future. 

Additional materials: www.superdatascience.com/598

SDS 598: Getting Kids Excited about STEM Subjects

This week, Mikiko Bazeley, Senior Software Engineer at Mailchimp joins the podcast to share her in-depth knowledge of MLOps: Machine Learning Operations. Tune in to hear her discuss what it entails, why it's so critical for the efficiency of any data science team, and the most important tools you need to master for career success in this field.

In this episode you will learn:
• What MLOps is [11:40]
• Mikiko’s role at Mailchimp and why MLOps is critical for the efficiency of any data science team [27:11]
• The three most important MLOps tools [32:15]
• The six most essential MLOps skills for data scientists [47:01]
• The key factors Mikiko looks when hiring engineers [1:07:31]
• Mikiko’s productivity tricks for balancing software engineering, content creation, and her athletic pursuits [1:13:20]

Additional materials: www.superdatascience.com/599

SDS 599: MLOps: Machine Learning Operations

6.22 inspects what brown can do for you (0:37), checks some Fantasy topline numbers (2:10), kicks around some football (4:34), presents “Stats 101 Lesson 0: Overview of '(Frequentist) Stats 101' and Descriptive Statistics” (5:50), and reviews Max Fried (29:21).

Episode 6.22 - Stats 101 Lesson 0

Neste episódio do podcat, os lambdas Ahirton Lopes e Matheus Vidal junto com o convidado Daniel Antonio, Data Warehouse Engineer na Stillfront Group, falam sobre Engenharia de Dados - o que é, onde se insere, qual seu futuro no mercado de trabalho e muito mais.  

Entre no nosso grupo do Telegram e compartilhe seus comentários com a gente: https://lb3.io/telegram

Feed do podcast: www.lambda3.com.br/feed/podcast Feed do podcast somente com episódios técnicos: www.lambda3.com.br/feed/podcast-tecnico Feed do podcast somente com episódios não técnicos: www.lambda3.com.br/feed/podcast-nao-tecnico

Pauta:
O que é Engenharia de Dados?
Academia x Indústria;
Boom e "hype" na área;
Onde Engenharia de Dados pode estar inserida?
Projetos interessantes e exemplos de aplicações em Engenharia de Dados.
Trabalhando e estudando Engenharia de Dados
Quais as principais diferenças quando comparado com desenvolvimento convencional ou até mesmo com outros perfis em dados?
Como normalmente se configura o trabalho de uma pessoa Engenheira de Dados, Especialista em Data Warehouse, Data Lake e outros papéis que lidam com Engenharia de Dados?
Descolamento Academia x Indústria na área. Estamos formando profissionais para atender às demandas em Engenharia de Dados?
 Visão sobre os desenvolvimentos recentes na área
O que esperar do mercado e do crescimento da adoção de boas práticas em Engenharia de Dados?
Observabilidade de dados:
Os dados estão atualizados?
Há dados faltantes?
E quando a falta de observabilidade atrapalha o trabalho em Engenharia de Dados?
Ainda haverá espaço para o trabalho da pessoa Engenheira de Dados no futuro?
LGPD e outras leis de proteção aos dados? Como essas novas práticas podem impactar o trabalho em Engenharia de Dados? 

Participantes:
Ahirton Lopes - @ahirton
Daniel Antonio - @danconte72
Matheus Vidal Grunewald - @matheus-vidal

Links:
What Is a Data Engineer: A Guide to This In-Demand Career
Definition: Data Engineer
Introducing the 5 Pillars of Data Observability

Edição:
Compasso Coolab

Créditos das músicas usadas neste programa:
Music by Kevin MacLeod (incompetech.com) licensed under Creative Commons: By Attribution 3.0 - creativecommons.org/licenses/by/3.0

Podcast

#312 - Engenharia de Dados

To quote Dr. Evil, "The details of our lives are quite inconsequential." What's important is that we like fantasy, as it applies to the genre and the game derived from baseball statistics. We also enjoy developing analytical and computational “tools” for supporting the latter habit. Our goal is to share our fantasy baseball tools with a little help from the fantasy genre for context, allusion, and (fire and) ice breaking. In doing so, we hope to broaden the way our audience approaches fantasy baseball. Our podcast presents our methods to the public in the spirit of OpenSource - through freely helping others we promote active conversation that improves our tools.

A Lambda3 é uma empresa de consultoria em processos de produção, treinamento e desenvolvimento de softwares focada em conceitos e metodologias ágeis, buscando o máximo de retorno sobre o investimento do cliente.

Nossa especialidade abrange todo o ciclo de desenvolvimento de software, cobrindo aspectos como gestão, análise, arquitetura e engenharia de software, utilizando práticas reconhecidas pelo mercado e garantindo mais qualidade e flexibilidade em todos os nossos serviços.

Com experiência comprovada no mercado, nossos profissionais são reconhecidos tanto no Brasil quanto no exterior, além de atuarem ativamente na comunidade como palestrantes nos principais eventos de tecnologia do país.

The Super Data Science podcast with Jon Krohn brings you the latest and most important machine learning, artificial intelligence, and broader data-world topics from across both academia and industry. As the quantity of data on our planet doubles every couple of years and this trend is set to continue for decades to come, there's an unprecedented opportunity for you to make an enormous impact in your lifetime. 

Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy. We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, and commercialization − everything you need to crush it with data science.

New tracks tagged #datascience