Silicon Valley Data Science, ML, AI Platform

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https://us02web.zoom.us/webinar/register/1417124428288/WN_4y_zWx7ITKarXG8OHXFtYA

Attention all aspiring data scientists! Magnimind Academy has one-of-its-kind mentorship and internship program for students lacking a portfolio but having the fundamentals. This fifteen-week boot camp is designed to provide you with:
-Real industry projects
-Expert data scientists
-Project-based intensive training
-Mock interviews -Resume polish
-Post-interview feedback

We will be hosting an information session to discuss the program in more detail. Whether you're a recent graduate or looking to transition into the field, this program is perfect for those who are serious about a career in data science.

Join us to learn more about this exciting program and get your questions answered. RSVP now to reserve your spot!

Agenda:
(PST) 10:00 am - 10:05 am Arrival and socializing and Opening
(PST) 10:05 am - 11:00 am "Info Session on Mentor-Led Data Science Internship Program"
(PST) 11:00 am - 11:10 am Q&A

About Dr. Murat Baday:

Dr. Baday is the co-founder of Magnimind Academy. He is passionate about everything related to data science, education, and entrepreneurship. He received a biophysics PhD from the University of Illinois and continued his studies at Stanford Univ as a Postdoc. He has published several papers and patents and he is the co-founder of several biotechs and AI startups.

About Dr. Yasin Ceran:

Yasin Ceran is passionate about all things data and holds a vast experience in data analysis, mathematical modeling and Apache Spark, and in SQL, Python and R. He is currently an associate professor at KAIST, South Korea, as well as teaching at San Jose State University at the heart of Silicon Valley. Yasin has worked rigorously on an array of data-related projects encompassing data mining, statistics, modeling, and is dedicated to sharing his experience and expertise with learners.

Please register using the zoom link to get a reminder:

https://us02web.zoom.us/webinar/register/1417124428288/WN_4y_zWx7ITKarXG8OHXFtYA

Webinar Passcode 901329

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https://us02web.zoom.us/webinar/register/4417121767538/WN_SzOUclX5Szu74d6pin1QoQ

In this session, we will embark on a journey to discover how SQL, a tried-and-true database querying language, seamlessly integrates with Python and LLMs to unlock new possibilities in data exploration, manipulation and insights generation. In addition, we will explore an open-source Python RAG (Retrieval-Augmented Generation) framework for SQL generation and related functionality.

Agenda:

(PDT) 11:45 am - 11:50 am Arrival, socializing, and Opening
(PDT) 11:50 am - 1:45 pm Tolulade Ademisoye "The Intersection of SQL (PostgreSQL) and Large Language Models for Data Query"
(PDT) 1:45 pm - 1:50 pm Q&A

About Tolulade Ademisoye

Tolulade is a Machine Learning Engineer building Semis at Reispar Technologies. He loves to simplify complex processes for people and businesses. Tolulade is a volunteer reviewer for SciPy 2024 conference, Scientific Computing with Python.

https://us02web.zoom.us/webinar/register/4417121767538/WN_SzOUclX5Szu74d6pin1QoQ

Webinar Passcode 189821

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https://us02web.zoom.us/webinar/register/3017138780213/WN_MjvWrSIYQy6wfGgU5Q3F5g

This presentation focuses on how organizations can embark on Gen AI journey from Prompt Engineering, RAG to Fine Tuning LLMs. It delves into how to unlock the power of retrieval-augmented-generation (RAG) for generative AI apps. Discover the art of designing, building, and optimizing RAG applications using Google AlloyDB Omni, a PostgreSQL-compatible database, in tandem with powerful LLMs like OpenAI, VertexAI, or other Open Source variants. Learn how enterprises can transcend from foundational RAG frameworks to Advanced RAG systems, unlocking unprecedented relevancy and accuracy in query responses. Delve into the best practices for deploying RAG applications and gain insights into the evaluation of RAG systems, ensuring optimal performance and maximum impact.

Agenda:

(PDT) 11:50 am - 12:00 pm Arrival, socializing, and Opening
(PDT) 12:00 pm - 1:00 pm Prasad Venkatachar "Unlocking generative AI in your enterprise with Google AlloyDB Omni and LLMs"
(PDT) 1:00 pm - 1:15 pm Q&A

About Prasad Venkatachar

Prasad Venkatachar is Sr Director - Solutions Engineering & Products at Pliops. He is focused on Solutions and Product strategy and leading and driving AI/GenAI, Data, Analytics & Storage solutions with partners. He has launched multiple industry-leading Data & AI/ML products & solutions collaborating with Microsoft, IBM, Oracle, Cloudera, and ISV partners to grow revenue & gain market share at Lenovo & HPE. He also served as a Microsoft Data and AI Partner Advisory Council Member and Member of Lenovo Technology Innovation. Served fortune 500 enterprise customers as SME to deliver business value outcomes for Datacenter and Cloud deployments. He has good experience and certified with Multiple Cloud (AWS/Azure/GCP/IBM) and Database (Oracle/DB2/Azure Data) and AI/Gen AI certifications. A regular speaker in Industry Conferences: Microsoft Ignite, Oracle Open World, Developer conferences: Pass Summit, Oracle users group, Flash Memory Summit, SNIA & Gartner Conference

https://us02web.zoom.us/webinar/register/3017138780213/WN_MjvWrSIYQy6wfGgU5Q3F5g

Webinar Passcode 216172

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https://us02web.zoom.us/webinar/register/5117080164625/WN_EPMw1tZGTD-SxWkSxJpBLg

In the era of information overload, recommendation systems have emerged as essential tools for filtering and personalizing content, thereby enhancing user experience across various digital platforms. These systems employ sophisticated algorithms to analyze user preferences, behaviors, and interactions to suggest items ranging from products and movies to news articles and academic papers. This talk aims to demystify the underlying mechanisms of recommendation systems, highlighting key techniques such as collaborative filtering, content-based filtering, and hybrid approaches. We will explore the challenges faced in developing effective recommendation systems, including issues of data sparsity, scalability, cold start, and ensuring diversity and fairness in recommendations. Furthermore, the talk will delve into the ethical considerations and the impact of bias in recommendation algorithms. By providing a comprehensive overview of recommendation systems, this talk seeks to inspire future research and development efforts aimed at creating more intelligent, transparent, and user-centric solutions.

Agenda:

(PDT) 11:45 am - 11:50 am Arrival, socializing, and Opening
(PDT) 11:50 am - 1:45 pm Khojasteh Mirza "Navigating the Complexity of Recommendation Systems: Techniques and Challenges"
(PDT) 1:45 pm - 1:50 pm Q&A

About Khojasteh Mirza

Khojasteh Mirza is a Master of Engineering student at Cornell Tech, specializing in Electrical and Computer Engineering with a focus on Data Science and Applied Machine Learning. With a rich academic background, including a Bachelor of Technology in Mechatronics Engineering from NMIMS University, Khojasteh has excelled academically, securing a Merit Scholarship and achieving high honors. His technical skills encompass a wide array of data science technologies, and his professional experience includes impactful roles as a Project Research Assistant at the Indian Institute of Technology Bombay, a Data Analyst at AIRMO Gmbh and Ozibook and most recently, responsible for developing recommendation systems for Cognitii, a learning app for neurodivergent individuals. Khojasteh's work spans innovative projects in healthcare industry developing predictive models for Parkinson’s disease in collaboration with Tata Consultancy Servicesdemonstrating his ability to apply data science for real-world impact.

https://us02web.zoom.us/webinar/register/5117080164625/WN_EPMw1tZGTD-SxWkSxJpBLg

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