Data Science

Blog Series on Gen AI for Executives

Leave a Comment / Artificial Intelligence, Executives, Learning resources /

Welcome to the series! Following is a series that will address these goals: Executive LearningEnhancing knowledge and skills in Data Science and Gen AI. Appreciating Usage PatternsUnderstanding how these technologies are being applied across different industries. Recognizing RisksIdentifying potential challenges and risks associated with Data Science and Gen AI. Best Practices for AdoptionSharing strategies and […]

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Develop Web Apps and Deploy ML Models using Streamlit: A Comprehensive Guide

1 Comment / Data Science, For Data Scientist, Learning resources, Machine Learning, Python /

In this comprehensive guide, we will explore the world of web app development and ML model deployment using Streamlit. Whether you are a data scientist, machine learning engineer, or web developer, this blog post is tailored to provide you with a step-by-step approach to building interactive web applications that leverage the power of ML models.

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Experience “no code” ML and AI

Leave a Comment / Artificial Intelligence, Executives, Learning resources, Machine Learning, No Code /

Hello! Hope you enjoy this playfully serious session on “no code” We will be using these posts in sequence [1] Experience “no code” ML https://playfullyserious.com/index.php/2023/06/30/experience-no-code-machine-learning/ [2] Experience “no code” ML deployment https://playfullyserious.com/index.php/2023/07/01/no-code-ml-deploying-a-model-and-testing/ [2] Experience “no code” AI https://playfullyserious.com/index.php/2023/07/02/experience-no-code-ai/

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Experience “No code” AI

3 Comments / Artificial Intelligence, Careers, Data Science, Executives, No Code /

Overview In this lab, you will use Flowise AI which is built on langchain to create some applications. This lab intends to be a gentle, guided introduction to the possibilities presented by AI. After completing this lab, you will have enough familiarity with the tools used and basic concepts to continue exploring on your own. I plan

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No Code ML: Deploying a model on Azure ML Studio

Leave a Comment / Data Science, Machine Learning, No Code /

This is part II of the lab using Azure ML Studio. The first part is in this link. Open the California House Price Prediction experiment. Click “Run”, then click “Set up as a web service”, then click “Predictive Web Service (Recommended)”, then click Run the Predictive Web Service Experiment Drag and drop the “Select Columns

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Experience “No Code” Machine Learning – Regression

2 Comments / Data Science, Deep Learning, Executives, Machine Learning /

Overview In this lab, you will use Azure Machine Learning to train, evaluate, and publish a Machine Learning model. This lab intends to be a gentle, guided introduction to core ML concepts. After completing this lab, you will have enough familiarity with the platform and basic ML concepts to continue exploring on your own. I

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Understanding multicollinearity

Leave a Comment / Data Science, For Data Scientist, Machine Learning /

In this post, the following questions are covered. Let me know if there are other aspects that you wish to see included. What is multicollinearity? Pearson Linear Correlation Coefficient measures the strength of linearity in relationship between two numeric variables. If we extend this to involve multiple variables we are referring to multicollinearity. How does

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Exploring courses in Data Science

Leave a Comment / Data Science, Learning resources, Machine Learning, Python /

There are many programs available addressing the unique needs of different segments of learners. Typically, these can be studied using the following attributes: ·        Full-time or weekend ·        Delivery modes: Classroom, Online Live, E-learning, Hybrid ·        Focus areas: Data Science, Data Engineering, Industry, Technology ·        Eligibility or Learner profile: Fresh graduates, working professionals, executives ·        Campus placement (Y or N)

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How to select your data science capstone project?

Leave a Comment / Data Science, Learning resources, Machine Learning /

Every course in data science ends with a capstone project which requires learners to apply various concepts covered along the way. This project is also a great addition to their resumes. Obviously, from both learning as well as career prospects angles this is an important step. This post covers three aspects of capstone projects: The

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