#Loops Data Analytics Platform

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Stay tuned and follow @datawithashok for the latest updates.!!

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How I built this data analytics project that uses LLMs to interpret multimodal data (KPI images)! ↳ Pulled the KPI images from a PDF ↳ Connected to OpenAI’s GPT-4 nano ↳ Input prompt & images into LLM ↳ Wrote the results to a report PDF (and I did it without any code too 😉) I used @knimesoftware to put together all the steps visually and create this analysis! It’s free and open source, so you can do it too! KNIME owns the entire data analytics pipeline and makes it really easy to follow the logic from raw data to final output. And it has so many data connections so you can pull data from spreadsheets, databases, APIs, cloud services, and more! Try KNIME today! #data #dataanalytics #knime #project #ai

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Get help from the developer community with the #GoogleDeveloperProgram forums. ⁠ ⁠ ✨ Dive into deeper discussions⁠ ✨ Get feedback on your code⁠ ✨ Network and knowledge share with others in the community⁠ ⁠ Connect with the community and start collaborating at the link in our bio.

Follow @analytics.with.miraj and comment "Python" and I will share you the entire end to end roadmap with tutorial links to play around with instantly. As a senior data analytics I am more than happy to guide you all into the world of python and data analytics in case of any career related doubts feel free to reach out to me directly in my DMs or mail me. [Python roadmap , Data Analytics , Python , Data science , Freshers , Experienced , Interviews , power-BI , SQL ] #dataanalytics #hiring #fresher #python What is python?? Python is a popular programming language for data analytics because it is easy to learn and powerful. It helps analysts clean, analyze, and visualize data using libraries like Pandas, NumPy, and Matplotlib. Python is widely used to find insights, automate analysis, and support data-driven decisions. 1️⃣ Python Basics • Variables, data types, loops, functions 2️⃣ Core Libraries • NumPy → numerical operations • Pandas → data cleaning & manipulation 3️⃣ Data Visualization • Matplotlib, Seaborn → charts & insights 4️⃣ SQL + Python • Read/write data from databases 5️⃣ Exploratory Data Analysis (EDA) • Missing values, outliers, trends 6️⃣ Statistics Basics • Mean, median, probability, hypothesis testing 7️⃣ Machine Learning (Basics) • Regression, classification (Scikit-learn)

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