AI & Data Science Tech Blog
Top 3 Trending Agentic AI Frameworks: LangGraph vs AutoGen vs Crew AI
Comparing 2024's top agentic AI frameworks: LangGraph, AutoGen, and CrewAI. Learn when to use these frameworks—and when to skip them—from an AI strategist who's implemented both custom and framework-based solutions. Get past the hype and make the right choice for your use case, whether you're prototyping or deploying to production.
Top 3 Predictions for Enterprise Generative AI: What to Expect in 2025
Explore the key trends shaping enterprise generative AI in 2025. Learn how generative AI will become as common as search, how autonomous AI agents will begin to make a limited impact, and why robust AI governance frameworks will be critical for safe and effective deployment. Stay ahead of the curve and strategically plan your enterprise AI strategy for next year.
Microsoft Copilots Explained: Are These AI Tools Worth Your Money?
Curious about Microsoft’s new AI Copilots? Discover what these tools can do, how they can enhance your productivity, and whether they’re worth the investment. Dive into our detailed review and decide if Microsoft Copilots are the right fit for you!
AWS Generative AI: How To Get Started With Powerful LLMs for Business
Navigating the world of AWS Generative AI? This practical guide breaks down the rise of generative AI and how AWS tools like Amazon Bedrock can be harnessed effectively to use LLMs for business.
Use Cases for ChatGPT - How to use LLMs For Your Business
Unlock the transformative power of AI for your business with Large Language Models (LLMs) like ChatGPT. 🚀 Dive into our comprehensive guide to leverage this AI revolution, from customer support to finance, and stay ahead in the competitive landscape. Master the 7 pivotal steps to integrate, secure, and scale LLMs in any enterprise setting. 🔗 #DemocratizedAI #ChatGPTforBusiness #AIinEnterprise
Excel Alternative: Want More Capable Data Analytics Software Used By GE, For Free?
Sure, Microsoft Excel is perfect for entering data in rows and columns. But what if you want to quickly find practical meaning in your data that allows you to take action and make better data-driven decisions? For example, what if you wanted to learn how many steps you should take to sleep better tonight based on your smartwatch data history? Here’s what you need to know.
Gartner Magic Quadrant for Data Science and Machine Learning Platforms 2021 Made Simple
Want to know who Gartner thinks are the top AI companies in 2021, and why? Estevan McCalley & Ken Sanford break down Gartner's 46-page report for you in less than 5 minutes (and try to entertain you along the way 😀). Here's what you need to know!
Feature Store: Uncover Uber's Secret to Large Scale Machine Learning
Most data science projects never make it to production. Fortunately, you can now easily deploy machine learning models like Uber. Here's what you need to know.
Machine Learning is Like a Baby
Ever wonder what machine learning is? Estevan McCalley simplifies machine learning with 3 key similarities and 3 important differences between babies and machine learning.
Machine Learning Operations: 3 Challenges Evaluating Machine Learning Models
How model drift impacted the KPIs of two businesses. Challenges, solutions, and outcomes.
Data Science, Machine Learning, and AI Analytics Platforms to Secure Funding in 2020
In spite of a tumultuous year caused by the COVID-19 pandemic, these advanced analytics technology vendors closed funding rounds in 2020. Congratulations!
Docker for Data Scientists Made Simple: Why Pay for Data Science Software?
Here's how you can get started in one-click for free.
Snowflake vs Databricks: Where Should You Put Your Data?
Software ate the world, turned it into data, and now it’s suffering from indigestion. Fortunately, cloud offerings from Databricks & Snowflake are here to help. Here's what you need to know.
Datagrom Magic Surfboards For Cloud Data Science & Machine Learning Platforms
An alternative review to Gartner and Forrester of the cloud machine learning platforms: Amazon AWS SageMaker, Microsoft Azure Machine Learning, and Google Cloud AI Platform.
Released in 2020: Meet AWS SageMaker Studio, Azure Machine Learning Studio, & GCP AI Platform
Review of machine learning platforms released in 2020: Amazon AWS SageMaker Studio, Microsoft Azure Machine Learning Studio, and Google Cloud AI Platform.
Databricks IPO in 2021? The Next Data Science & Machine Learning Platform to go Public
Map of data science nerve centers across the US in 2020. Interpretation, and projections post COVID-19.
Data Science Hot Spots in the US: And What to Expect Post COVID-19
Map of data science nerve centers across the US in 2020. Interpretation, and projections post COVID-19.
Ranked: Infographic of the Fortune 500 with the Most Data Scientists
Infographic Ranking: Businesses & Sectors of Fortune 500 with the Most Data Science & Machine Learning Projects
Top 3 Data Science Challenges to Operationalize Machine Learning: Insider Stories
Want to add data science and machine learning capabilities to your arsenal (or just make more data-driven decisions)? If so, I commend you! While the rewards can be plentiful, quite often so are the roadblocks to achieving this goal. To help with your journey, I wrote this article to give you a preview of the top challenges you will likely face, so that you can immediately start to make adjustments to your business in order to facilitate this effort.