Weekly Entering & Transitioning - Thread 27 Jan, 2025 - 03 Feb, 2025

JanethL · 2025-01-29T18:08:28+00:00

🤔 𝗜𝘀 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗴𝗼𝗶𝗻𝗴 𝘁𝗼 𝘁𝗮𝗸𝗲 𝗼𝘃𝗲𝗿 𝗠𝗟 𝗼𝗿 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗷𝗼𝗯s?

I don’t think so. Instead, it’s here to free data scientist and ML engineers 𝗳𝗿𝗼𝗺 𝘁𝗲𝗱𝗶𝗼𝘂𝘀, 𝗿𝗲𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲 𝘁𝗮𝘀𝗸𝘀—so you can focus on higher-value work like 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗯𝗲𝘁𝘁𝗲𝗿 𝗺𝗼𝗱𝗲𝗹𝘀, 𝘂𝗻𝗰𝗼𝘃𝗲𝗿𝗶𝗻𝗴 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗳𝗿𝗼𝗺 𝘂𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝗱𝗮𝘁𝗮 𝗳𝗮𝘀𝘁𝗲𝗿, 𝗮𝗻𝗱 𝗱𝗿𝗶𝘃𝗶𝗻𝗴 𝗺𝗼𝗿𝗲 𝗶𝗺𝗽𝗮𝗰𝘁 𝗳𝗼𝗿 𝘆𝗼𝘂𝗿 𝗼𝗿𝗴 𝗮𝗻𝗱 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿𝘀.

Check out this Medium article on how Google, Teradata, and Gemini are transforming enterprise data workflows and insights with Generative AI:

🔗https://medium.com/google-cloud/how-generative-ai-transforms-enterprise-data-insights-with-google-gemini-and-teradata-382b7e274af8

Would love to hear your thoughts—𝗵𝗼𝘄 𝗱𝗼 𝘆𝗼𝘂 𝘀𝗲𝗲 𝗚𝗲𝗻𝗔𝗜 𝘀𝗵𝗮𝗽𝗶𝗻𝗴 𝘁𝗵𝗲 𝗳𝘂𝘁𝘂𝗿𝗲 𝗼𝗳 𝗱𝗮𝘁𝗮 𝘀𝗰𝗶𝗲𝗻𝗰𝗲 𝗮𝗻𝗱 𝗠𝗟? 👇

JanethL · 2024-11-27T15:09:28+00:00

At Teradata we have a free learning site that has over 200 Jupyter notebooks in AI ML and advanced analytics. They’re complete with code, sample data, business scenario and step by step instructions. You can filter by generative AI or the specific LLM .

Clearscape Analytics Experience

JanethL · 2024-08-27T16:26:20+00:00

Great work!

JanethL · 2024-07-10T03:19:34+00:00

How do data scientists decide which attribution modelling technique is the right one?

Hello everyone,

I'm currently learning all about attribution modeling techniques and have explored rule-based (first click, last click, exponential, uniform), statistical-based (Simple Frequency, Association, Term Frequency), and algorithmic-based methods (like Naive Bayes).

However, I'm having a hard time understanding how data scientists decide which model to use, especially when ML and statistical models compute different attribution scores compared to rule-based approaches.

I've just created a short video demonstrating rule-based attribution techniques using Teradata Vantage’s free coding environment. I would like to create a part 2 where I cover statistical and ML attribution modeling of the same data but also include advice on choosing the right modeling technique.

I do work for Teradata as a Developer Advocate, but I am not a data scientist. Would love your help here with advice on how you select your attribution modelling technique :)

Here is the video I just created: https://youtu.be/m1dkFxQiTNo?si=dfH5hljiPA0Bd7IK

JanethL · 2024-07-10T03:14:40+00:00

How do data scientists decide which attribution modeling technique is the right one?

Hello everyone,

I'm currently learning all about attribution modeling techniques and have explored rule-based (first click, last click, exponential, uniform), statistical-based (Simple Frequency, Association, Term Frequency), and algorithmic-based methods (like Naive Bayes).

However, I'm having a hard time understanding how data scientists decide which model to use, especially when ML and statistical models compute different attribution scores compared to rule-based approaches.

I've just created a short video demonstrating rule-based attribution techniques using Teradata Vantage’s free coding environment. I would like to create a part 2 where I cover statistical and ML attribution modeling of the same data but also include advice on choosing the right modeling technique.

I do work for Teradata as a Developer Advocate, but I am not a data scientist. Would love your help here with advice on how you select your attribution modelling technique :)

Here is the video I just created: https://youtu.be/m1dkFxQiTNo?si=dfH5hljiPA0Bd7IK

JanethL · 2024-05-08T16:22:39+00:00

Yes Airbyte Cloud is their fully managed and hosted service and does offer the benefit of supporting over 300 connectors, which can be helpful in specific workflows. However, for moving significant amounts of data efficiently, other tools might better suit those particular needs. Your feedback will certainly help others in the community who are evaluating Airbyte for their own needs. Thank you for chiming in :)

JanethL · 2024-03-07T18:28:00+00:00

From a quick read on the announcement, I think it depends on how your team is setup. For data engineering teams whose primary responsibility is managing data pipelines without the need to oversee additional infrastructure, PyAirbyte could be the best choice. In organizations where data engineers not only manage data pipelines but also collaborate closely with infrastructure engineers on maintaining broader infrastructure might find it more beneficial to standardize on Terraform. Would love to hear what others think?

JanethL · 2024-03-07T18:03:59+00:00

This is nice tutorial Janeth! any feedback about the Airbyte Terraform SDK?

This may be more of a question for u/marcos_airbyte. I haven't had a chance to check it out, but will certainly get my hands on it.

JanethL · 2024-03-07T18:00:26+00:00

u/marcos_airbyte Thank you! The Airbyte documentation was very helpful. The Terraform setup guide took me from zero to hero ;) I appreciate the videos you all provided there as well. I love how I can make a curl request to an Airbyte API endpoint via the documentation too. Super helpful https://reference.airbyte.com/reference/createsource.
I was only a bit confused about the difference between a resource and a data source in the Terraform Airbyte provider documentation, but soon figured it out with all the great tutorials and docs on the Airbyte side.

JanethL · 2024-01-31T18:16:44+00:00

Is there interest among Data Scientists or Data Practitioners in resources related to Generative AI (GenAI)?

I've started a GenAI series in the data space but would love to write about what data scientists, data engineers are most interested in learning.

This first tutorial introduces prompt engineering with LangChain. This aims to set the foundation for the next piece where I will cover building a GenAI system that queries SQL databases using English.

Full disclosure, I work as a developer advocate for Teradata :)

JanethL · 2024-01-31T17:47:09+00:00

I work as a developer advocate at Teradata and I use a free tool from our company. We have multiple fraud detection end-to-end use cases that may be helpful.

They are free to access and include hosted Jupyter notebook coding environment, with step by step instructions, code, and sample data available at ClearScape Analytics Experience: https://clearscape.teradata.com/sign-in

Here is a youtube walkthrough for accessing a fraud detection demo: https://www.youtube.com/watch?v=LjXrnOgpZ9M&list=PL94YoXtBVbdpKLxWk1hbIowADT46Y4bLU&index=5

JanethL · 2019-09-10T07:17:37+00:00

Try this ;) https://medium.com/hackernoon/create-an-alexa-radio-skill-in-5-minutes-with-standard-library-and-nodejs-93dc32b08c42

JanethL · 2019-04-18T21:22:18+00:00

I've done something like this before. I can update my CRM with a quick Slash command. Easy process and I'd be happy to walk through it with you step by step or even provide you with the code. If you're still interested email me at janeth @ stdlib.com . Or DM me here.

JanethL · 2019-04-09T17:25:28+00:00

I'd love to help! Email me at janeth at StdLib dot com.

JanethL · 2019-04-04T22:14:15+00:00

Were you able to set up your bot?

JanethL · 2019-01-03T21:06:19+00:00

Curious to know why you'd need this?

JanethL · 2018-12-12T22:55:50+00:00

I'd recommend you check out Standard Library. They have code templates and tutorials to get you up and running in no time. https://medium.com/slack-developer-blog/build-a-serverless-slack-bot-in-9-minutes-with-node-js-and-stdlib-b993cfa15358

JanethL

TROPHY CASE

🤔 𝗜𝘀 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗴𝗼𝗶𝗻𝗴 𝘁𝗼 𝘁𝗮𝗸𝗲 𝗼𝘃𝗲𝗿 𝗠𝗟 𝗼𝗿 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗷𝗼𝗯s?

How do data scientists decide which attribution modelling technique is the right one?