This episode is part 2 of our discussion with Jonathan Bechtel, a data science instructor at General Assembly. In this episode we  tackle the following topics:

  • The job application/hiring process for data science

      - Do bootcamps and graduate programs offer a career services office?

      - Training for technical screenings

      - How long does a job search take?

  • How is applying into a data science job different now vs 3 or 4 years ago? 

😎ABOUT US:

Laura and Vijay are data scientists who enjoy talking about data and sharing their experiences, which is why they started this podcast. Laura worked in credit risk modeling and experimental design. She is also an amateur silversmith. Vijay worked on Deep Learning NLP models and recommender systems. He also loves learning new things, like French. On Deep Data Dive, they will share their work experiences, discuss data science fundamentals, and chat with guests, and more.

👍🏼 PODCAST MISSION STATEMENT:

Welcome to Deep Data Dive! Data is the new oil and data scientist is the sexist job of the 21st century (at least according to Harvard Business Review…). If you want to learn more, you’re in the right place! Follow us as we discuss our work experiences, review key data science concepts, learn new concepts, and chat with guests. We will tell you everything they know about the field, getting a job as a data scientist, and what the job is like. We hope you will follow our journey, have some fun, laugh, and learn some data science along the way.

🎙PODCAST (Streaming FREE on 17+ platforms!)

   • Amazon Music: https://bit.ly/DDD-Amazon

   • Apple Podcast: https://bit.ly/DDD-Apple

   • Spotify: https://bit.ly/DDD-Spotify

   • iHeart Radio:https://bit.ly/DDD-iHeartRadio

   • Google Podcast: https://bit.ly/DDD-Google

🗣 LET'S CONNECT:

Twitter: @DeepDataDive (www.Twitter.com/DeepDataDive) 

*Tweet us your questions and comments! We want to engage with our audience.

🌐 VISIT OUR WEBSITE: 

www.DeepDataDive.live

👥 HOSTS: Laura & Vijay

🎥 VIDEO PRODUCTION:

Dana Donovick, Passion Possible, LLC.

dana@passionpossible.com • 206-222-0740

https://twitter.com/PassionPossible

https://twitter.com/DanaDonovick

Special Guest: Jonathan Bechtel, data science instructor at General Assembly (Worked with multiple companies in NYC and other cities)

(Lots of work with programmatic data extraction and pipelining)

How did we all get into data science?

  • Jonathan, Vijay, Laura

Different ways to get into data science

  • Bootcamp programs

  • Traditional masters

  • Self Taught

😎ABOUT US:

Laura and Vijay are data scientists who enjoy talking about data and sharing their experiences, which is why they started this podcast. Laura worked in credit risk modeling and experimental design. She is also an amateur silversmith. Vijay worked on Deep Learning NLP models and recommender systems. He also loves learning new things, like French. On Deep Data Dive, they will share their work experiences, discuss data science fundamentals, and chat with guests, and more.

👍🏼 PODCAST MISSION STATEMENT:

Welcome to Deep Data Dive! Data is the new oil and data scientist is the sexist job of the 21st century (at least according to Harvard Business Review…). If you want to learn more, you’re in the right place! Follow us as we discuss our work experiences, review key data science concepts, learn new concepts, and chat with guests. We will tell you everything they know about the field, getting a job as a data scientist, and what the job is like. We hope you will follow our journey, have some fun, laugh, and learn some data science along the way.

🎙PODCAST (Streaming FREE on 17+ platforms!)

   • Amazon Music: https://bit.ly/DDD-Amazon

   • Apple Podcast: https://bit.ly/DDD-Apple

   • Spotify: https://bit.ly/DDD-Spotify

   • iHeart Radio:https://bit.ly/DDD-iHeartRadio

   • Google Podcast: https://bit.ly/DDD-Google

🗣 LET'S CONNECT:

Twitter: @DeepDataDive (www.Twitter.com/DeepDataDive) 

*Tweet us your questions and comments! We want to engage with our audience.

🌐 VISIT OUR WEBSITE: 

www.DeepDataDive.live

👥 HOSTS: Laura & Vijay

🎥 VIDEO PRODUCTION:

Dana Donovick, Passion Possible, LLC.

dana@passionpossible.com • 206-222-0740

https://twitter.com/PassionPossible

https://twitter.com/DanaDonovick

Episode 3 : Data science and Machine Learning

In this episode, we juxtapose the different types of Machine Learning: supervised, unsupervised, semi-supervised, and reinforcement.

What is the difference between data science and machine learning?

• Machine learning is a sub-discipline within data science
• Machine learning is an application of artificial intelligence
• Machine learning is predictive analytics
• Prescriptive analytics and recommending a path forward

The different types of machine learning: supervised, unsupervised, semi-supervised, and reinforcement learning

Supervised machine learning: data is labeled and we know the outcome, using a predictive model and comparing your predicted results to the labeled outcomes.

• Classic examples of churn and spam vs non-spam
• Classification vs regression problems and how they differ

Unsupervised machine learning: data is not labeled and we don’t know the outcome.

• Clustering using a distance metric is involved, and we can get the attributes of different clusters
• Latent dich allocation (LDA) for topic modeling (categories not defined beforehand)

Semi-supervised machine learning

• Turning an unsupervised program into a supervised learning problem
• How do we determine accuracy and precision of semi-supervised machine learning?

Reinforcement learning

• Self-driving cars examples
• A car will make mistakes, a penalty system will prevent those mistakes from re-emerging in the future
• The AI agent continuously learns based on a set of penalties that are imposed
• There will be a growth in reinforcement learning in the future

🎙PODCAST: Listen on the go, free!

Spotify  •  Amazon Music  •  Google Podcast  •  iHeart Radio

👥ABOUT US:

Laura and Vijay are data scientists who enjoy talking about data and  sharing their experiences, which is why they started this podcast. Laura  worked in credit risk modeling and experimental design. She is also an  amateur silversmith. Vijay worked on Deep Learning NLP models and  recommender systems. He also loves learning new things, like French. On  Deep Data Dive, they will share their work experiences, discuss data  science fundamentals, and chat with guests, and more.

📱LET'S CONNECT:

Twitter: @DeepDataDive (www.Twitter.com/DeepDataDive)

🎥VIDEO PRODUCTION & DESIGN:

• Dana Donovick, Passion Possible, LLC.
• dana@passionpossible.com • 206-222-0740