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#Eda Data Mining Techniques Reel by @jessramosdata (verified account) - Comment "project" for my full video that breaks each of these projects down in detail with examples from my own work.

If you're using the Titanic, Ir — Comment “project” for my full video that breaks each of these projects down in detail with examples from my own work. If you’re using the Titanic, Iris, or COVID-19 dataset for data analytics projects, STOP NOW! These are so boring and over used and scream “newbie”. You can find way more interesting datasets for FREE on public data sites and you can even make your own using ChatGPT or Claude! Here are the 3 types of projects you need: ↳Exploratory Data Analysis (EDA): Exploring a dataset to uncover insights through descriptive statistics (averages, ranges, distributions) and data visualization, including analyzing relationships between variables ↳Full Stack Data Analytics Project: An end-to-end project that covers the entire data pipeline: wrangling data from a database, cleaning and transforming it. It demonstrates proficiency across multiple tools, not just one. ↳Funnel Analysis: Tracking users or items move from point A to point B, and how many make it through each step in between. This demonstrates a deeper level of business thinking by analyzing the process from beginning to end and providing actionable recommendations to improve it Save this video for later + send to a data friend!

#Eda Data Mining Techniques Reel by @scalewithsubhashish (verified account) - Day24/365 of making ₹0 to ₹10Cr (Data Miner)

#startuplife #business #enterprenuership #sales — Day24/365 of making ₹0 to ₹10Cr (Data Miner) #startuplife #business #enterprenuership #sales

#Eda Data Mining Techniques Reel by @datapronezone - Exploratory Data Analysis (EDA) is the first crucial step in any data analysis. It's all about understanding the data-detecting patterns, spotting ano — Exploratory Data Analysis (EDA) is the first crucial step in any data analysis. It’s all about understanding the data—detecting patterns, spotting anomalies, and discovering relationships between variables. By using visualization tools and summary statistics, EDA allows us to ask the right questions before diving deeper into complex modeling. Whether you’re looking for trends, outliers, or just a clearer picture of the dataset, EDA helps unlock valuable insights that drive better decisions. . . . . . . More videos on this topic are cooking! Stay tuned! . . . . . Follow @datapronezone for more data related videos! . . . . . “Happy Learning!” #DataScience #ExploratoryDataAnalysis #DataVisualization #Analytics #Insights #DataExploration” #datapronezone #dataanalytics #machinelearning

#Eda Data Mining Techniques Reel by @sundaskhalidd (verified account) - Comment 'Projects' to get 5 Data Scientist Project ideas and a plan 👩🏻‍💻

♻️ repost to share with friends. Here is how to become a data scientist i — Comment ‘Projects’ to get 5 Data Scientist Project ideas and a plan 👩🏻‍💻 ♻️ repost to share with friends. Here is how to become a data scientist in 2026 and beyond 📈 the original video was 4 min Andi had to cut it down to 3 because instagram. Should I do a part 3v what are other skills that you would add to the list and let me know what I should cover in the next video 👩🏻‍💻 #datascientist #datascience #python #machinelearning #sql #ai

#Eda Data Mining Techniques Reel by @muskan.khannaa - You DO NOT need to learn everything to become a Data Engineer.
People often prepare for mid-level roles while applying for entry-level roles.

Here's — You DO NOT need to learn everything to become a Data Engineer. People often prepare for mid-level roles while applying for entry-level roles. Here’s what actually mattered for me in the beginning when switching from testing to a data engineer role. 1. SQL(non-negotiable): You’ll need to know the basics and complexities of sql along including subqueries and window functions. If you’re not strong in SQL, you won’t be able to move forward in interviews. 2. Python concepts basics like lists, dictionaries, sets and basic problem solving. You can solve questions in other languages too but I’d suggest Python as it’s easy to learn. You don’t need hardcore DSA for most entry-level Data Engineering roles, but DSA is definitely important. 3. Data warehousing concepts like facts vs dimension, star vs snowflake schema, SCD Type 1,2 etc. Understanding concepts and what data warehousing is and why it’s there mattered more than tools. 4. ETL and data pipeline understanding. How data is extracted, transformed, loaded is the CORE of Data Engineering. You don’t need spark understanding in the beginning, just the understanding of how data flows in and out. 5. System design basics, not like design twitter/uber. Simple understanding of how data moves end to end and overall understanding of data eco-systems. No deep design is expected at entry-level. 6. Pick any one cloud. Don’t chase all clouds, just any one cloud and cover its basics because you’d most likely be working on some cloud in your work. I moved from Testing to Data Engineering by focusing on these basics, instead of trying to learn every other tool out there, and it is still the very core of Data Engineering which one must know to crack interviews. Save this if you’re planning to make a switch into Data Engineering. . . . . . [data engineering roadmap, entry level data engineer preparation, switching to data engineering, testing to data engineering, data engineer interview preparation, sql for data engineering, python basics for data engineer, data engineers for beginners, microsoft data engineer] #dataengineer #dataengineering

#Eda Data Mining Techniques Reel by @chrisoh.zip - The best projects serve a real use case

Comment "data" for all the links and project descriptions

#tech #data #datascience #ml #explore — The best projects serve a real use case Comment “data” for all the links and project descriptions #tech #data #datascience #ml #explore

#Eda Data Mining Techniques Reel by @danangkumara - Belajar Data Science dan Machine Learning jadi lebih mudah dengan Orange Data Mining! 🍊💻 Tutorial lengkap ini akan membantu Anda memahami analisis d — Belajar Data Science dan Machine Learning jadi lebih mudah dengan Orange Data Mining! 🍊💻 Tutorial lengkap ini akan membantu Anda memahami analisis data interaktif tanpa coding. Langkah mudah untuk menguasai dunia Data Science! 🚀 #BelajarDataScience #OrangeDataMining #DataScience #MachineLearning #AIProjects #TutorialDataScience #DataAnalysis #TeknologiTerkini #BelajarMachineLearning #InteractiveData #InovasiTeknologi #DataMiningTools #AICommunity #DataEnthusiast #FutureTech

#Eda Data Mining Techniques Reel by @the.datascience.gal (verified account) - Here's a roadmap to help you go from a software engineer to a data scientist 👩‍💻 👇

If you're tired of writing vanilla apps and want to build ML sy — Here’s a roadmap to help you go from a software engineer to a data scientist 👩‍💻 👇 If you’re tired of writing vanilla apps and want to build ML systems instead, this one’s for you. Step 1 – Learn Python and SQL (not Java, C++, or JavaScript). → Focus on pandas, numpy, scikit-learn, matplotlib → For SQL: use LeetCode or StrataScratch to practice real-world queries → Don’t just write code—learn to think in data Step 2 – Build your foundation in statistics + math. → Start with Practical Statistics for Data Scientists → Learn: probability, hypothesis testing, confidence intervals, distributions → Brush up on linear algebra (vectors, dot products) and calculus (gradients, chain rule) Step 3 – Learn ML the right way. → Do Andrew Ng’s ML course (Deeplearning.ai) → Master the full pipeline: cleaning → feature engineering → modeling → evaluation → Read Elements of Statistical Learning or Sutton & Barto if you want to go deeper Step 4 – Build 2–3 real, messy projects. → Don’t follow toy tutorials → Use APIs or scrape data, build full pipelines, and deploy using Streamlit or Gradio → Upload everything to GitHub with a clear README Step 5 – Become a storyteller with data. → Read Storytelling with Data by Cole Knaflic → Learn to explain your findings to non-technical teams → Practice communicating precision/recall/F1 in simple language Step 6 – Stay current. Never stop learning. → Follow PapersWithCode (it's now sun-setted, use huggingface.co/papers/trending, ArXiv Sanity, and follow ML practitioners on LinkedIn → Join communities, follow researchers, and keep shipping new experiments ------- Save this for later. Tag a friend who’s trying to make the switch. [software engineer to data scientist, ML career roadmap, python for data science, SQL for ML, statistics for ML, data science career guide, ML project ideas, data storytelling, becoming a data scientist, ML learning path 2025]

#Eda Data Mining Techniques Reel by @ai_with_thiru (verified account) - Comment 'EDA' to get step by step guide. Exploratory Data Analysis.
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Machine Learning, EDA, Data Analysis, Data Manipulation, ML Models
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#mlmo — Comment 'EDA' to get step by step guide. Exploratory Data Analysis. . . . Machine Learning, EDA, Data Analysis, Data Manipulation, ML Models . . #mlmodels #eda #dataanalytics #machinelearning #datascience

#Eda Data Mining Techniques Reel by @topclickmediasa (verified account) - Use the Instant Data Scraper to quickly pull data from websites!

#scrape #data — Use the Instant Data Scraper to quickly pull data from websites! #scrape #data

#Eda Data Mining Techniques Reel by @data_with_anurag (verified account) - 🚨 Want to become a Data Analyst but don't know where to start? 👀

I've got you covered - Microsoft has launched a dedicated learning path with free — 🚨 Want to become a Data Analyst but don’t know where to start? 👀 I’ve got you covered — Microsoft has launched a dedicated learning path with free resources to help you master Data Analytics step by step! 📊 💬 Comment “DATA” and I’ll DM you the complete roadmap + official Microsoft resources. ✅ Beginner to advanced topics covered ✅ 100% FREE learning materials ✅ Certificate-ready path to build your career 🔥 This is your sign to start learning data analytics the right way — straight from Microsoft! 🚀

#Eda Data Mining Techniques Reel by @ilmudata - Kalo namanya pasaran enak ga muncul data pribadi kita cuma kalo nama kita unik atau ada info spesifik wah kelar, dari pddikti pun bisa 😅😅😅

#belaja — Kalo namanya pasaran enak ga muncul data pribadi kita cuma kalo nama kita unik atau ada info spesifik wah kelar, dari pddikti pun bisa 😅😅😅 #belajarngoding #tutorial #python #datascienceindonesia #datascience #ilmudata #dataanalisis #programer #bigdata #analyst Source : I do not own this video. They belong to their rightful owner. Tiktok: https://vt.tiktok.com/ZSYsmNHC9/

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