Datasciencewithsam

It was great to be recognized by Microsoft AI Community as the recipient of Beta Learner Impact Award for Creative Innovation last month!

Just launched my latest guided project on Coursera, a leading online education platform, focusing on the large text summarization process using the popular framework, LangChain 🤖

By taking this project, learners will gain essential skills such as👇

✅ understanding the utilization of OpenAI model via Langchain,
✅ exploring the idea of prompt templates to enhance summarization process, and
✅ gaining insights on how to integrate summarization model with a Streamlit web app.

In just under 2 hours, you will have the basic knowledge to kick off your journey in the realm with respect to summarizing large documents for academic researchers and industry professionals.

If this sounds interesting, then I wish you good luck in advance for taking the course. And, if you do end up taking the course, don't forget to provide feedback to help me with my instructor journey. Let's learn and grow together!

GenAI Summarization with Langchain: Summarize Text Documents Complete this Guided Project in under 2 hours. In this guided project, you will learn the art of text summarization using the well-known GenAI framework, ...

The podcast🎙️ is back with its second session. The new episode features a thought-provoking discussion on the importance of in the era.

Special thanks to Marina Polupanova for sharing her valuable perspectives on this topic during the session. Her insights shed light on the crucial role of data scientists in the current era of AI and its impact on various industries.

Don't miss out on this informative episode! You can listen to it on various media platforms. Check out the links below to access it:

1️⃣Apple 👉🏼 https://podcasts.apple.com/us/podcast/data-science-with-sam/id1587954336?i=1000644041565

2️⃣ Amazon Music 👉🏼 https://music.amazon.com/podcasts/ff82ee49-c8af-49b3-83aa-c3e156017eed/episodes/f6d63ee3-09b2-4964-a515-3a3104bdcf5d/data-science-with-sam-growing-technology-footprints-in-insurance-sector?ref=dm_sh_IeO2ynK3Wg8bOHK2ZDfEN6dRB

👉🏼 If you are interested to be featured in my next episode and initiate conversations focusing on Data Science, AI and Scientific Research then feel free to DM me on LinkedIn.

📍Disclaimer: The views and opinions expressed in this podcast are solely those of the individuals involved and do not necessarily represent those of any organizations.

As we approach the end of 2023, it’s time to reflect on some of the milestones that I achieved throughout the year👇

✅ One of the key cornerstones of my professional endeavors was moving from the finance/insurance space to the pharmaceutical marketing area, which aligned with my career interests. It’s been an exhilarating journey in my new organization CMI Media group and I’m looking forward to learning more in 2024.

✅ I was also rewarded with the experience of releasing my first self-guided project for learners around the world, associated with Coursera. The project has already received 70+ enrollments, and I am expecting more students to kick off their AI journey by taking the project in the forthcoming months.

✅ My personal YouTube and podcast channel “DataScienceWithSam” gained a substantial amount of attention, boasting 2k+ subscribers and 8k+ downloads. I’m planning to release more digital content in the upcoming year as I manage time from my professional and personal commitments. Thank you for all the support to help continue my journey of raising awareness about the intersection of science, technology, and generative AI.

✅ Lastly, I had the privilege of being invited as a speaker to the AI in Finance summit and getting the opportunity to network with some of the brightest minds in the industry space.

📍 I am beyond thankful for all the professional and academic support I received from my peers, LinkedIn contacts, and other networks that helped me become a better version of my professional self.

Looking forward to 2024 for more professional adventures ➡️

📣 My first Coursera guided project “TensorFlow for Beginners: Basic Binary Image Classification” is available for public access now.

It was a unique experience working with world’s leading online education platform provider to design and develop course contents on the Rhyme platform that give learners an interactive hands-on experience on the topic.

This course is designed for newbies who want to take their first step into the world of computer vision and By taking this project, learners will gather basic knowledge about building neural network model using popular Python library TensorFlow that can be used for image classification purpose.

I dedicated this project to my pet dog 🐕 whose images have been used as a sample to test the efficacy of the model that learner will develop during the project.

If this sounds interesting to you, then go ahead and sign up for this project via the link below, which will help you to learn basic neural network model building skills in less than 2 hours.

TensorFlow for Beginners: Basic Binary Image Classification Complete this Guided Project in under 2 hours. The goal of this project is to introduce beginners to the basic concepts of machine learning using ...

Have you ever heard about the technical term "Observability"?

Listen to my latest podcast episode that shed some lights on this new technical concept by addressing the following relevant topics:

✅ What Observability means in the context of modern software development and system monitoring? How does Observability differ from traditional monitoring and logging practices?
✅ Why has Observability gained so much attention in recent years? What are the driving factors behind its increasing popularity?
✅ From cybersecurity perspective, what role does Observability play in identifying and mitigating potential threats or vulnerabilities?
✅ How do you see the future of Observability evolving in the next few years from the context of recent AI innovation surge?
✅ What resources or learning opportunities would you recommend for individuals or teams interested in diving deeper into the topic of Observability?

📍 Podcast links:
Apple 👉🏼 https://podcasts.apple.com/us/podcast/data-science-with-sam/id1587954336?i=1000623550107

Amazon Music 👉🏼 https://music.amazon.com/podcasts/ff82ee49-c8af-49b3-83aa-c3e156017eed/episodes/b9e0d176-ef8b-42d8-a345-4010e09b490b/data-science-with-sam-what-is-observability?ref=dm_sh_QQNxitoPsayJ8nyrsjCwBvIHG

DISCLAIMER: The views and opinions expressed in this podcast are solely those of the host(s) or guest(s) and do not necessarily reflect the policy or position of any organization. The podcast is intended to provide general educational information and entertainment purposes only.

No matter how great your generative AI strategy is, you won’t be able to make a robust AI app if the underlying data has a lot of quality issues.

Take good care of your data and it will do wonders for you 🙂

This article is worth reading as it attempts to uncover the strategies that companies can consider to tap into the potential of 🤖 by utilizing proprietary data.

In my opinion, these are the advantages of transforming the theoretical concepts into more actionable items for organizations👇

☑️ Leveraging company’s proprietary information would enable data scientists/AI engineers to bring further innovative ideas to drive business decisions that aligned with organizational long-term objectives.

☑️ Developing a homegrown LLM model or generative AI app 💻 instead of using an external pre-existing model (such as GPT-4, BERT etc.) would reduce the risk of data security breach or infiltration attack by hackers 🛡️

☑️ Building a knowledge-based platform 📚 that would assist internal employees to gather information about organization’s intellectual capital or institutional knowledge based on their job functionalities in more convenient way.

⚠️Caveats:

Building a LLM model from scratch is expensive as it would require significant amount of investments to build framework and hire a team of SMEs consist of data scientists and NLP/AI experts.

Therefore, it is necessary to prepare a blueprint of ROI metrics from budgetary perspective before kicking off the generative AI endeavor for your respective organizations.

📍Important Note 📝

In the midst of rapid technological growth, organizations may aim for bringing generative AI to enhance processes that accelerate business decisions WITHOUT eliminating the existence of human-based job roles that require human intellect.

Check out this article and share it with your business and technology leaders to get their perspectives on this. Happy reading!

How to Train Generative AI Using Your Company’s Data Leveraging a company’s proprietary knowledge is critical to its ability to compete and innovate, especially in today’s volatile environment. Organizational innovation is fueled through effective and agile creation, management, application, recombination, and deployment of knowledge assets and kn...

Hey everyone!

I've been getting a lot of DMs for guidance on the field of and so I decided to take action on it.

I'm excited to help folks out and give back to the community via Topmate.io Don't hesitate to reach out if you have any questions or just want to say hi!

Booking link 👉🏼 https://topmate.io/samdey