Cloud Dominant LLC

04/03/2025

🚨 New Video Drop!

I just launched a walkthrough of my latest project:

🔍 Predicting Crime Likelihood in Baltimore City using Python + Streamlit.

With over 200,000 arrest records, this project explores reported incidents across different districts and times of day. In the video, I:

📊 Break down how the data was cleaned and prepared

🧠 Walk through the prediction model

💻 Demo the interactive app I built in Streamlit

📈 Share key takeaways and next steps for improving the model

⚠️ Disclaimer: This project is for educational purposes only — it predicts reported crime incidents, not actual crimes, and is meant to explore technical workflows in data, not real-world policing strategies.

🎯 I invite others in the data community to download the dataset and build their own versions!

📹 Watch the video below.

👨‍💻 Let me know what you’d build with this kind of dataset!

🚨 New Video Drop!I just launched a walkthrough of my latest project:🔍 Predicting Crime Likelihood in Baltimore City using Python + Streamlit.W...

03/28/2025

🏡 Predicting Home Prices with Data Science: Harford County Edition 🔍📊

In this video, I dive into my latest machine learning project where I analyze nearly 19,000 home sales across Harford County over the past five years! 🗓️📈

You’ll see:

✨ How I cleaned and prepped the data for accurate predictions

🏷️ Why home condition categories really matter

🔍 A deep dive into specific property analyses

⚠️ The real-world challenges of aligning predictions with actual market trends

Whether you’re a data nerd, real estate enthusiast, or just curious about the power of predictive modeling — this one’s for you. 💬 I’d love to hear your thoughts on my process and any ideas to improve it!

👉🏽 Watch, learn, and let’s build better predictions together.

🏡 Predicting Home Prices with Data Science: Harford County Edition 🔍📊In this video, I dive into my latest machine learning project where I analyze nearly ...

03/25/2025

🔍 Episode 2: Leveling Up My Home Price Prediction Model in Aberdeen, MD 🏡💡

In this video, I take my real estate machine learning model to the next level! 🚀
I added new predictive features to improve price accuracy:
✅ Above Grade Square Feet
✅ Below Grade Square Feet
✅ Central Air
✅ Mortgage Rate (👀 YES — and wait until you see how higher rates unexpectedly correlated with higher home prices!) 📈

To integrate mortgage rates, I pulled in 5 years of historical data, converted it to monthly values, and joined it to my training dataset. This step alone added a valuable time-based signal to help my model understand market cycles. 🧠📊

👉🏽 Coming up next:
• 🧱 Condition analysis using Computer Vision & GenAI on property descriptions
• 🌳 Adding lot size
• 🗺️ Expanding to Harford County, then Maryland, and eventually the entire U.S.
• 🎯 Digging deeper into the impact of finished vs. unfinished basement square footage
• 🔁 Retraining and retesting model accuracy

If you’re into real estate, data science, or AI-powered tools that will shape the future of property valuation, follow this journey! 💼🏠💻

Let’s predict smarter, not harder.

👇🏽 Watch now, subscribe, and follow for more

🔍 Episode 2: Leveling Up My Home Price Prediction Model in Aberdeen, MD 🏡💡In this video, I take my real estate machine learning model to the next level! ?...

03/22/2025

🔍 Can AI predict home prices accurately? I built a model to find out.

In this video, I dive into one of my latest machine learning projects: predicting real estate prices using data from Aberdeen, Maryland. 🏡📊

I walk through how I:
• Collected and cleaned local housing data
• Selected key variables for the model
• Built a regression model using sklearn, and visualized insights with seaborn, matplotlib, and pandas
• Deployed the entire experience in a user-friendly Streamlit app

One of the challenges I uncovered? The model initially undervalued waterfront properties, which taught me a lot about feature engineering and the need for more nuanced data inputs.

This is just the beginning—I’m continuing to refine the model, and I’d love your input. 💬
👉 Check out the predictions and let me know what you’d tweak or improve.

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In this video, I share my recent work on machine learning and AI projects, specifically focusing on real estate price prediction using data from Aberdeen, Maryland. I walk through the process of setting up a model, including data cleaning and variable selection, and I highlight some challenges I've....

12/25/2024

Hey Salesforce enthusiasts! 👋 At Cloud Dominant, we LOVE helping both technical and non-technical viewers understand the powerful tools Salesforce has to offer! 💡

📽️ In this video, we’re diving into the basics of Salesforce’s Forecasting function! Here’s what you’ll learn:

✅ Forecast Settings – How to get started with forecasting the right way.
✅ Forecast Hierarchy – Understand how roles and permissions come into play.
✅ Revenue Forecast Example – Watch us break it down step by step.
✅ Forecast Categories – What they are and why they matter.
✅ Sales Manager’s View – A peek at the forecast list view of a salesperson from their manager’s perspective.

💼 Whether you’re a Salesforce admin, developer, or just curious about CRM, this video is packed with tips to take your forecasting to the next level.

👉 Check it out and let us know your thoughts in the comments!
🔗 https://youtu.be/W3wW0qWqKwg?si=oWANcu4eco2pn5o_

💬 We’re always open to your questions and feedback, so don’t hesitate to reach out!

Let’s dominate the cloud together! ☁️⚡
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Hey Salesforce enthusiasts! 👋 At Cloud Dominant, we LOVE helping both technical and non-technical viewers understand the powerful tools Salesforce has to of...

12/25/2024

🌟 Empowering Small Businesses & Nonprofits with Salesforce! 🌩️

Are you a small to medium-sized business or nonprofit using Salesforce to manage your relationships and opportunities? This video is for YOU! 🎯

We break down the 5 essential standard objects—Lead, Account, Contact, Case (sometimes) and Opportunity—to show how they work together to streamline your processes, save time, and drive growth. 💼✨

Whether you’re just starting or looking to maximize your Salesforce investment, this is your guide to mastering the basics and unlocking your potential. 💡

👉 Watch now and see how Cloud Dominant can help you tailor Salesforce to your unique needs. Let’s make CRM work for YOU! 🌟

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🌟 Empowering Small Businesses & Nonprofits with Salesforce! 🌩️Are you a small to medium-sized business or nonprofit using Salesforce to manage your relatio...

07/22/2024

🏚️ Where does your Salesforce Administration live? Personally, I have seen a few different teams house the Salesforce squad, but most fall outside of the original intent when the CRM spend was made.

🌟 Business or Enterprise Systems: This is where they manage multiple SaaS products, from ERP to Marketing to CRM. How CRM gets handled here is a matter of what they consider to be the most important.

🌟 Sales and Marketing: The Sales and/or Marketing teams like to use it to drive Sales, but because of Salesforce's nuance, it gets overshadowed by other tools.

🌟 IT/Software Engineering: This is obviously the most technical of the groups, so the focus can (but not always) become about complexity over user experience.

🌟Operations: This is a very broad title, but some operations teams house smaller teams that specialize in internal tools. But for smaller teams, Salesforce can even get handled by HR!

🌟 Salesforce: An entire team of Salesforce Pros (or just one individual) can be hyperfocused, stay abreast of current needs, and also be very good at helping the org meet its intended purpose. They can also have direct communication with end users.

🌟 Some companies even have a CRM Manager or Director. In the former, this person acts more like a Product Manager that is also hands on with the system. I have even seen a company that had a Director of CRM that had little (if any) interaction with the Salesforce team!

I have no problem with any of these setups (except for HR! 😉), and have come to find that none are perfect. Salesforce is a cross-functional tool, handling Sales, Marketing, Operations, Support, Finance, Legal, and more. One way to supplement this complexity is with a Product or Project Manager, where impactful initiatives can be developed and driven towards completion.

Where does your CRM solution live? Does it work well for you? Where do you think it should reside? Let me know below! ⬇️