H.Mati
@MissHelenah
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Data Alchemist ๐ | AI & ML Enthusiast ๐ค | AI Analytics | Data Protection | Crafting insights with curiosity & charm โจ
Global
Joined July 2019
Happy New Year ! 2026, may it be our softest and strongest chapter yetโฆ.๐ซถ
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Donโt overthink AWS project building. โข Start with one service โข Deploy something simple first โข Use the Free Tier wisely โข Break things โ learn from logs โข Add services one at a time โข Focus on architecture, not fancy UI โข Document decisions & trade-offs โข Clean up
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A single full table scan can destroy MySQL's cache. Here's how MySQL cleverly prevents this... When a full table scan happens, it can flush out all valuable cached pages and replace them with pages that are often never needed again. This 'cache pollution' forces subsequent
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๐ Docker is Go โธ๏ธ Kubernetes is Go ๐ ๏ธ Terraform is Go ๐ Prometheus is Go ๐ Grafana is TypeScript โ๏ธ Jenkins is Java ๐ Ansible is Python ๐ด Chef is Ruby ๐ญ Puppet is Ruby ๐ ELK Stack (Elasticsearch, Logstash, Kibana) is Java and Ruby ๐ Nagios is C ๐พ Splunk is C++ โ๏ธ AWS CLI
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1. Rich Dad Poor Dad โ teaches you about assets. 2. Psychology of Money โ teaches you about behavior. 3. Atomic Habits โ teaches you about systems. Read them in that order for maximum impact.
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Git Branching Cheat Sheet: Git Flow branching strategy every DevOps / developer should know ๐ What is a Git Branch? Ans:- A Git branch is a separate line of development that lets you: โ
Build new features โ
Fix bugs safely โ
Experiment freely โ
Without breaking production
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Today's Work: 1. Fullstack Project(Coding Platform)โ
(3hr) - Created the submission schema - Created the route for submitting the problem. 2. DSAโ
(1hr) - Solved 2 easy problem using unordered map. Resources : https://t.co/BirM3yCUVq
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I said my goal this year is to Land you a Data gig Right?? Now letโs get you ready!! Data Analytics Job-Ready Checklist: 1. Core Skills (Must Have) โขExcel: Pivot tables, XLOOKUP, data cleaning โขSQL: SELECT, JOIN, GROUP BY, subqueries โขPower BI / Tableau: KPIs, dashboards,
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Top 50 Linux Commands You Must Know 1. ls - view contents of directory (list) 2. pwd - path of the current directory 3. cd - change directoryn 4. mkdir - make new directory 5. mv - move files / rename files 6. cp - copy files 7. rm - remove files 8. touch - create blank new
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Morning guys, happy new year #Datafam. Quick one - if youโre trying to break into data analytics this year, I got you. Been dropping free content on YouTube for a minute now. Real projects. Real walkthroughs ๐๐น๐ฟ๐ฒ๐ฎ๐ฑ๐ ๐ด๐ผ๐ ๐๐ถ๐ฑ๐ฒ๐ผ๐ ๐ผ๐ป: โ Excel dashboards (sales
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How AWS Manages Container Services โ AWS manages containerized applications using fully managed services that simplify deployment, scaling, and operations. โ These services remove the need to manage container hosts manually while providing high availability and security. Core
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We chose MongoDB because it was 'web scale' and schema-less seemed perfect for rapid iteration. Two years later: - Data inconsistencies required manual cleanup scripts - Queries that worked with 1M records failed with 10M - Schema migrations were more painful than SQL ALTER
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๐จNew Year. Fresh skills. Zero barriers.๐จ Iโve made all my tech learning guides each at just $1 - so you can pick exactly what you need and learn at your own pace. https://t.co/mnORvDJkU5 โข Cloud โข DevOps โข Kubernetes โข AWS โข Terraform โข Linux โข Python โข AI (Quick
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How I Designed an MLOps Project in 25 Days Without Any Tutorials. MLOps practices + Agentic AI + Classic ML On Sunday, 4 Jan 2026 Subscribe: https://t.co/cjX8meQc8Z My first Substack article of 2026 is a practical guide to the behind-the-scenes design of my recent flagship
MLOPS PROJECT IS LIVE ๐ Stock-Agent-Ops (Classical ML + Agentic AI) ๐ GitHub repo: https://t.co/WgovKSgVjZ This project helps you understand how to design production-level real-time ML projects. That's why I chose stock data. It has a very clean README file. Take a look if
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SQL Query Cheat Sheet (Beginner) SELECT * FROM table WHERE condition ORDER BY col DESC LIMIT n GROUP BY col HAVING filter JOIN tables COUNT(), SUM(), AVG() Learn these = 80% of real-world SQL queries.
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Kubernetes (To The Point) Series - Part 3
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Backend Request Lifecycle โ Simplified Client request โ DNS โ resolves service location โ Load Balancer โ traffic distribution โ API Gateway โ auth, rate limits, routing โ Middleware โ logging, tracing, validation โ Controller / Handler โ request intent โ Service
Kubernetes Core Components - Simplified Cluster basics โ API Server โ the front door โ etcd โ cluster state & truth โ Scheduler โ Pod placement logic โ Controller Manager โ desired vs actual state โ kubelet โ node-level execution โ kube-proxy โ Service networking โ
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Donโt overthink AWS architecture. โข Learn how requests flow โข Learn compute โ where code runs โข Learn storage โ where data lives โข Learn networking โ how services talk โข Learn security โ who can access what โข Learn scalability โ load balancers & auto scaling โข Learn
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