#Erwin Data Modeler Tutorials

Let’s build a Machine Learning Model for Sentiment Analysis! 🤖💬 Using this dataset that I found online, I was able to experiment with building ML Models using Tensorflow and Python. 💻 This is the first time I’ve made a video about building an ML Model, so let me know if you’d like to see more! 🎥 After testing this, I was pretty impressed with the results. Would you like to see that video? 👀

Data modeling in Power BI is like building a “map” for your data so tables can talk to each other. With the right relationships (for example, using a Product Key), your visuals become more accurate, structured, and easier to analyze. When the data structure is solid, Power BI from Microsoft isn’t just about good-looking dashboards, it delivers real insights. #PowerBI #DataModeling #BusinessIntelligence

Пишите АГЕНТ под роликом, если хотите внедрить ИИ-автоматизации в ваши бизнесы

Comment “PROJECT” and I’ll send you the link. Everyone says “build projects” to learn coding… but almost no one explains how to actually start. This is exactly how I planned and structured a full project in just one day using Verdent (@verdent__ai) Instead of guessing what to do, I generated a complete system design — including architecture, tech stack, and how everything connects — before writing a single line of code. Then I created a step-by-step implementation plan with file structure, endpoints, and the exact order to follow. I even mapped out the data flow and edge cases early, so I knew what could break before I started building. This is where most developers struggle: 👉 turning ideas into real projects 👉 understanding system design 👉 knowing what to build first With Verdent AI, you can go from idea → plan → working product in minutes, while learning real-world development workflows. If you’re learning programming, building portfolio projects, or trying to level up as a developer, this is something you should definitely try. Save this for later and start building smarter 🚀 #verdentai #aiagent #softwareengineering #Verdent #VerdentAI #Vibecoding #AIcoding

Deep Learning & Machine Learning models (like neural networks) process input data as arrays of numbers (1D, 2D, 3D). For example, an image is converted into a matrix where each value represents pixel brightness. These matrices pass through layers of matrix multiplications, weights, biases, and activation functions. During training, the model tweaks these parameters to minimize the loss function (error). Step by step, the network learns patterns, transforms numbers, and outputs predictions 🔥 That’s how machines “learn” from data... powering breakthroughs in computer vision, AI, and robotics. Credits: @3blue1brown 👉 Follow us @deeprag.ai for more content like this! . . . #deeplearning #machinelearning #datascience #neuralnetworks #computervision #artificialintelligence #python #programming #ml #bigdata #robotics #education #computerscience #dataanalytics

Building a deep learning model is essentially building a sophisticated math pipeline. Modern AI models use automation to turn raw data into decisions through geometry. Imagine your input - like a photo or a sentence - as a piece of clay. Each layer of the model acts as a hand that reshapes that clay. The "magic" is actually a grid of numbers called a matrix. As the data passes through these layers, it gets multiplied and shifted. This process highlights important patterns and ignores the noise. Training isn't a mystery; it is simply the model adjusting those grid numbers. It keeps tweaking the math until the final shape matches the correct answer. Raw data goes in, geometry happens, and a prediction comes out. Understanding these mathematical layers allows us to build leaner, faster AI agents that process business data with surgical precision. C: 3blue1brown Comment CLEAR if this helped you understand. #ArtificialIntelligence #NeuralNetworks #AIImplementation

If you are breaking into AI creating synthetic data for supervised fine tuning is a skill you should learn.

Lets build a forecasting model #aiapps #aitechnology #contentcreation #ai2025 #digitaltools

Prompt Variables offer a new way of prompting. Check out the step-by-step tutorial by @kenvreman - now on the Weavy YouTube channel.

Learn how time series models are built, from preparing historical data and training models to using them on new data

💡Type ‘ER’ in the comments & I’ll DM you the full YouTube video on ER diagrams! 🎯 Struggling to understand ER Diagrams? 😵‍💫 Let me make it SUPER EASY for you! In Part 6 of my DBMS series, I break down what an Entity-Relationship Diagram is and how to draw one step by step — with simple logic and no boring jargon! 📊✍️ Save it, share it, and master ER diagrams like a pro! 🤓🔥 #dbms #erdigram #sqltutorial #computersciencestudents #cse #codinglife #reelsforstudents #learndbms #codingisfun #programmingreels #studentreels #trending #explore #reelsinstagram #ai

Free AI Data Engineering Project for Beginners 🦜⛓ Create your AI Data assistant with Data BigQuery + LangChain + VertexAI 💬 Comment “AI” to get the tutorial! We will build together a sample Python application that will be able to understand and respond to human language queries about the relational data stored in your Data warehouse. 🏆 This could be a great feature if you want to enable or showcase to your management how to talk to the data in a natural way and make their life easier. 🦾 It’s basically creating your own AI Data assistant #data #dataengineer #bigdata #programming #datascience #ai #ml #artificialintelligence #langchain #llm #chatgpt #bigquery #gcp #cloudtechnology #learntocode