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Full Stack Developer | Project Manager | Executive Assistant

41: Followers

Full Stack Developer | Project Manager | Executive Assistant

Cover image for Full Stack Approach

Full Stack Approach

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Cover image for AI & Full-Stack Developer | LLMs, Machine Learning

AI & Full-Stack Developer | LLMs, Machine Learning

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Cover image for I chose to create a

I chose to create a cohesive visual experience combining Virtual Assistance, Tree Crown Detection and Segmentation Systems, and creative artistic storytelling. The goal was simple to build a short narrative across four key scenes that feels human, modern, and technically grounded. Each scene reflects how I blend automation, computer vision concepts, and creative direction into functional, visually compelling work. I do not just execute tasks. I design workflows and use AI as a creative partner to deliver impact. If you are looking for someone who can bridge AI, automation, and creative production, I would love to connect. #VirtualAssistant #AIContent #ComputerVision #CreativeAI #VideoAdCreation #AutomationSpecialist #MorphicAI #TechContent #AIWorkflow #ContraTalent:

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Cover image for Mastering Virtual Assistance: Modern Tools for Efficient Ope...

Funny how skills stack over time. My background as a Virtual Assistant still shows up daily, staying organized, thinking ahead, and executing cleanly. I bring that same mindset into my work at Kokorick, where we build with modern tools like LLMs and focus on strong systems. Grateful for the path. #StartupLife #VirtualAssistant #Operations #LLM #RemoteWork

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Pimpri-Chinchwad, India

Power BI Expert | Turning Raw Data into Actionable Insights

New to Contra

Power BI Expert | Turning Raw Data into Actionable Insights

Cover image for Data Analytics Project | BlinkIT

Data Analytics Project | BlinkIT Grocery Sales Analysis Excited to share my latest Data Analytics project ,where I analyzed BlinkIT Grocery Sales Data and delivery data to uncover meaningful business insights 📈 📊 What I worked on: Analyzed sales performance across product categories, outlet types, sizes, and locations Identified top-performing item categories and customer preferences Studied the impact of outlet size, establishment year, and visibility on sales Converted raw data into actionable insights and business recommendations 💡 Key Insights: Fruits & Vegetables, Snack Foods, and Frozen Foods drive maximum sales FOR FULL PROJECT VIST GIT HUB –( https://lnkd.in/d34sdAPz )

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Cover image for I’m excited to share my

I’m excited to share my latest Data Analytics project where I analyzed Customer Shopping Behavior to uncover trends in sales, demographics, and purchasing habits.This project was a great exercise in building a complete data pipeline. The Tech Stack: Python (Pandas & NumPy): Used in Jupyter Notebooks for initial data exploration and statistical analysis. PostgreSQL: Utilized for rigorous data cleaning, querying, and structuring the dataset for analysis. Power BI: Built an interactive dashboard to visualize key metrics like seasonal trends, subscription impacts, and category performance. Project Highlights: ✅ Data Cleaning: Leveraged PostgreSQL and Pandas to handle missing values and standardize categorical data.

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Cover image for Venezuela’s Oil Reserves Analysis Dashboard

Venezuela’s Oil Reserves Analysis Dashboard 📊 I am excited to share my latest data analytics project focusing on the energy sector. Using a dataset covering 23 reservoirs, I designed a comprehensive dashboard to track production capacity and resource distribution in Venezuela. Key Features: ✅ Real-time Metrics: Tracking the 390.50 Billion total barrels in reserve. ✅ Granular Analysis: Production capacity breakdown by reservoir name and oil grade (Extra Heavy to Light). ✅ Stakeholder Mapping: Visualizing the production sum by major operators. Tools Used: [pandas(jupyter notebook)/mysql(for analysis and cleaning of data), Power BI / Excel(for building dashboard)] I’d love to hear your thoughts or feedback on the dashboard design! must visit my github for full project -( https://lnkd.in/dYKdZ8J2 )

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Cover image for Data Analytics Project | BlinkIT

Data Analytics Project | BlinkIT Grocery Sales Analysis Excited to share my latest Data Analytics project ,where I analyzed BlinkIT Grocery Sales Data and delivery data to uncover meaningful business insights 📈 📊 What I worked on: Analyzed sales performance across product categories, outlet types, sizes, and locations Identified top-performing item categories and customer preferences Studied the impact of outlet size, establishment year, and visibility on sales Converted raw data into actionable insights and business recommendations 💡 Key Insights: Fruits & Vegetables, Snack Foods, and Frozen Foods drive maximum sales Medium-sized outlets outperform others in overall revenue FOR FULL PROJECT VIST GIT HUB –( https://lnkd.in/d34sdAPz ) Feedback and suggestions are always welcome!

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Data Analyst provided data driven decisions to stakeholders.

23: Followers

Data Analyst provided data driven decisions to stakeholders.

Cover image for House Price Analysis for Value Improvement

House Price Analysis for Value Improvement

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Cover image for Tanzanian Water Well Data Analysis Project

Tanzanian Water Well Data Analysis Project

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Cover image for Call Volume Prediction Model for Mtoto News

Call Volume Prediction Model for Mtoto News

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Cover image for https://github.com/Brene-m/AWS_Restatrt

https://github.com/Brene-m/AWS_Restatrt

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Faisal Ahmad Gifari

South Jakarta, Indonesia

Detail-oriented Virtual Assistant and Data Entry Specialist

Detail-oriented Virtual Assistant and Data Entry Specialist

Cover image for Machine Learning Model for Water Quality Classification

Machine Learning Model for Water Quality Classification

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Cover image for Sentiment Analysis Deployment for Restaurant Reviews

Sentiment Analysis Deployment for Restaurant Reviews

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Cover image for Streaming Platform Recommendation System Development

Streaming Platform Recommendation System Development

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Full Stack Machine Learning Expert

Full Stack Machine Learning Expert

Cover image for Auto-Labeling Images with Florence 2 and SAM

Auto-Labeling Images with Florence 2 and SAM

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Cover image for AI-Generated Imagery with Hugging Face Diffusion Models

AI-Generated Imagery with Hugging Face Diffusion Models

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Cover image for AI-Generated Imagery with Hugging Face Diffusion Models

AI-Generated Imagery with Hugging Face Diffusion Models

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Cover image for Football Video Analysis System with YOLO, OpenCV, and Python

Football Video Analysis System with YOLO, OpenCV, and Python

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Algiers, Algeria

Data Scientist

Data Scientist

Cover image for Forecasting Solar Energy Production

Forecasting Solar Energy Production

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Cover image for Arabic Manuscript Detection using Active learning

Arabic Manuscript Detection using Active learning

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Cover image for Customer Retention and Predictive Analytics System

Customer Retention and Predictive Analytics System

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40+ years programming experience including recent AI and ML.

6: Followers

40+ years programming experience including recent AI and ML.

Cover image for AI-Powered Fraud Detection Platform for Kaggle Contest

AI-Powered Fraud Detection Platform for Kaggle Contest

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Cover image for Lots of projects in the works! Too many really. Opus 4.5 has...

Lots of projects in the works! Too many really. Opus 4.5 has jammed my design episodes into hyper mode. I'm glad I heard Andrew Ng talk about the exhaustion after a day of working with agentic code helpers. That showed up months ago and I still didn't recognize. Now, having to hold so much in my mind at once while it is also growing at a recognizable pace is noticeably stressful. Here is my latest build, a useful agency for questions at high accuracy with 9 different agents available to work in tandem. Special thanks to my friend Enigma Specter who provided the original backend mechanisms. I salvaged his design with a nice web UI and added a web Researcher agent: https://guyzer.pythonanywhere.com/mrce/ You will need to register but it's just an email username and password, no verification loop yet. And you'll need an API key.

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Cover image for Cyclical Adversarial Stepwise Improvement CASI: Live Demo We...

Cyclical Adversarial Stepwise Improvement CASI: Live Demo We talk frequently about AI self-correction but few projects provide a robust architectural loop for it. CASI formalizes the process of non-linear refinement: The Generator proposes a solution or concept. The Critic applies structural pressure and targeted feedback. The system cycles automatically until Structural Coherence is reached. You can now test the CASI engine live and see how an autonomous refinement process delivers structurally superior output: Try the CASI web app here: https://guyzer.pythonanywhere.com/casi/

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Cover image for Further investigations of the Biology Latent Space.

Further investigations of the Biology Latent Space.

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Manideep racharla

Data Analyst turning Data insights into business impact.

5.0: Rating

2: Followers

Data Analyst turning Data insights into business impact.

Cover image for Optimizing Home Delivery in Small Grocery Stores

Optimizing Home Delivery in Small Grocery Stores

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Cover image for Parking Lot Utilization Analysis Dashboard

Parking Lot Utilization Analysis Dashboard

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Cover image for Predictive Analysis of Airline Delays Using Machine Learning

Predictive Analysis of Airline Delays Using Machine Learning

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Cover image for Stock Price and Trading Indicators Analysis

Stock Price and Trading Indicators Analysis

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