Data Science & Machine Learning

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Join this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free For collaborations: @love_data

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Tarmoq:Free Courses with Certificate - Python Programming, Data Science, Java Coding, SQL, Web Development, AI, ML, ChatGPT Expert Hindiston4 312 Taʼlim2 117...

📈 Telegram kanali Data Science & Machine Learning analitikasi

Data Science & Machine Learning (@datasciencefun) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 75 800 obunachidan iborat bo'lib, Taʼlim toifasida 2 117-o'rinni va Hindiston mintaqasida 4 312-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 75 800 obunachiga ega bo‘ldi.

16 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 924 ga, so‘nggi 24 soatda esa 38 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

Tasdiqlash holati: Tasdiqlanmagan
Jalb etish (ER): Auditoriya o‘rtacha 3.47% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.42% ini tashkil etuvchi reaksiyalarni to‘playdi.
Post qamrovi: Har bir post o‘rtacha 2 629 marta ko‘riladi; birinchi sutkada odatda 1 075 ta ko‘rish yig‘iladi.
Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 5 ta reaksiya keladi.
Tematik yo‘nalishlar: Kontent learning, accuracy, distribution, panda, dataset kabi asosiy mavzularga jamlangan.

📝 Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“Join this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free For collaborations: @love_data”

Yuqori yangilanish chastotasi (oxirgi ma’lumot 17 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Taʼlim toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.

75 800

Obunachilar

+3824 soatlar

+2197 kunlar

+92430 kunlar

2 629

Post ko'rishlar

~ 1 07524 soatlar

~ 1 41348 soatlar

3.47%

Muloqot nisbati

~ 3

Kuniga postlar

Ads index

beta

Postlar arxiv

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𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐬𝐭 𝐉𝐨𝐛 𝐎𝐩𝐞𝐧𝐢𝐧𝐠𝐬 𝐈𝐧 𝐌𝐲𝐧𝐭𝐫𝐚 🔥 Openings:- 50+ Qualification:- Any Graduate/Post Graduate Job Location:- Bangalore Salary:- 12LPA 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐏𝐫𝐨𝐜𝐞𝐬𝐬👇:- https://bit.ly/3ZGZMS9 Select your experience & Complete The Registration Process In the search box , Select the company name "Myntra "& Apply for jobs

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Industry Data Science vs Academia Data Science Comparing Data Science in academia and Data Science in industry is like comparing tennis with table tennis: they sound similar but in the end, they are completely different! 5 big differences between Data Science in academia and in industry 👇: 1️⃣ Model vs Data: Academia focuses on models, industry focuses on data. In academia, it’s all about trying to find the best model architecture to optimise a defined metric. In industry, loading and processing the data accounts for around 80% of the job. 2️⃣ Novelty vs Efficiency: The end goal of academia is often to publish a paper and to do so, you will need to find and implement a novel approach. Industry is all about efficiency: reusing existing models as much as possible and applying them to your use case. 3️⃣ Complex vs Simple: More often than not, academia requires complex solutions. I know that this isn’t always the case but unfortunately, complex papers get a higher chance of being accepted at top conferences. In industry, it’s all about simplicity: trying to find the simplest solution that solves a specific problem. 4️⃣ Theory vs Engineering: To succeed in academia, you need to have strong theoretical and maths skills. To succeed in industry, you need to develop strong engineering skills. It is great to be able to train a model in a notebook but if you cannot deploy your model in production, it will be completely useless. 5️⃣ Knowledge impact vs $ impact: In academia, it’s all about creating new work and expanding human knowledge. In industry, it is all about using data to drive value and increase revenue.

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𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗙𝗥𝗘𝗘 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗣𝗿𝗲𝗽𝗮𝗿𝗮𝘁𝗶𝗼𝗻 𝗚𝘂𝗶𝗱𝗲😍 | 𝗖𝗿𝗮𝗰𝗸 𝗬𝗼𝘂𝗿 𝗡𝗲𝘅𝘁 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄💫 Preparing for your first Data Analytics interview can feel overwhelming, but not anymore! 🚀 Here's your ultimate guide to crack it like a pro – from must-know SQL and Excel tips to problem-solving strategies and project insights. 📝 Start preparing smarter, not harder, and take your first step toward that dream job! 💼 𝐋𝐢𝐧𝐤👇: - https://bit.ly/3BOazC9 All The Best 💥

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Hey Guys👋, The Average Salary Of a Data Scientist is 14LPA 𝐁𝐞𝐜𝐨𝐦𝐞 𝐚 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐞𝐝 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐭𝐢𝐬𝐭 𝐈𝐧 𝐓𝐨𝐩 𝐌𝐍𝐂𝐬😍 We help you master the required skills. Learn by doing, build Industry level projects 👩‍🎓 1500+ Students Placed 💼 7.2 LPA Avg. Package 💰 41 LPA Highest Package 🤝 450+ Hiring Partners Apply for FREE👇 : https://tracking.acciojob.com/g/PUfdDxgHR ( Limited Slots )

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Data Science Interview Cheat Sheet! 🧠 1️⃣ Key Concepts Master statistics, machine learning, and programming basics. They’re always top priorities! 2️⃣ Essential Tools Know your way around Python, SQL, and data visualization platforms like Tableau or Power BI. 3️⃣ Real-World Projects Be ready to explain your projects—what problem you solved, how you did it, and the results you achieved! 🌟 4️⃣ Problem-Solving Skills Practice coding challenges and case studies.

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𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞 𝐉𝐨𝐛 𝐀𝐥𝐞𝐫𝐭 𝐀𝐭 𝐆𝐞𝐧𝐩𝐚𝐜𝐭 😍 Role:- Business Analyst - Data Science Qualification:- BE/B- Tech, BCA, MCA, BSc/MSc Work location: Bangalore Expected Salary:- 12 LPA 𝐀𝐩𝐩𝐥𝐲 𝐧𝐨𝐰👇:- https://pdlink.in/40nQWus Apply before the link expires

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Data Science Resolution for 2025

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𝐅𝐑𝐄𝐄 𝐌𝐚𝐬𝐭𝐞𝐫𝐜𝐥𝐚𝐬𝐬 𝐈𝐧 𝐇𝐲𝐝𝐞𝐫𝐚𝐛𝐚𝐝 😍| 4th & 5th Jan 2025 Learn Coding directly from JP Morgan, Microsoft Software Developers Join the free offline DEMO CLASS on the 4th and 5th of January - Expert Led Classes - 450+ Hiring Partners - Weekly Hiring Drives - 2000+ Students Placed 𝐑𝐞𝐠𝐢𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧 𝐋𝐢𝐧𝐤:👇- https://pdlink.in/4h1GzSg (You will get all the details after registering)

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🚨30 FREE Dataset Sources for Data Science Projects🔥 Data Simplifier: https://datasimplifier.com/best-data-analyst-projects-for-freshers/ US Government Dataset: https://www.data.gov/ Open Government Data (OGD) Platform India: https://data.gov.in/ The World Bank Open Data: https://data.worldbank.org/ Data World: https://data.world/ BFI - Industry Data and Insights: https://www.bfi.org.uk/data-statistics The Humanitarian Data Exchange (HDX): https://data.humdata.org/ Data at World Health Organization (WHO): https://www.who.int/data FBI’s Crime Data Explorer: https://crime-data-explorer.fr.cloud.gov/ AWS Open Data Registry: https://registry.opendata.aws/ FiveThirtyEight: https://data.fivethirtyeight.com/ IMDb Datasets: https://www.imdb.com/interfaces/ Kaggle: https://www.kaggle.com/datasets UCI Machine Learning Repository: https://archive.ics.uci.edu/ml/index.php Google Dataset Search: https://datasetsearch.research.google.com/ Nasdaq Data Link: https://data.nasdaq.com/ Recommender Systems and Personalization Datasets: https://cseweb.ucsd.edu/~jmcauley/datasets.html Reddit - Datasets: https://www.reddit.com/r/datasets/ Open Data Network by Socrata: https://www.opendatanetwork.com/ Climate Data Online by NOAA: https://www.ncdc.noaa.gov/cdo-web/ Azure Open Datasets: https://azure.microsoft.com/en-us/services/open-datasets/ IEEE Data Port: https://ieee-dataport.org/ Wikipedia: Database: https://dumps.wikimedia.org/ BuzzFeed News: https://github.com/BuzzFeedNews/everything Academic Torrents: https://academictorrents.com/ Yelp Open Dataset: https://www.yelp.com/dataset The NLP Index by Quantum Stat: https://index.quantumstat.com/ Computer Vision Online: http://www.computervisiononline.com/dataset Visual Data Discovery: https://www.visualdata.io/ Roboflow Public Datasets: https://public.roboflow.com/ Computer Vision Group, TUM: https://vision.in.tum.de/data/datasets

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🚀𝐁𝐨𝐨𝐬𝐭 𝐘𝐨𝐮𝐫 𝐂𝐚𝐫𝐞𝐞𝐫 𝐰𝐢𝐭𝐡 𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭’𝐬 𝐅𝐫𝐞𝐞 𝐂𝐨𝐮𝐫𝐬𝐞𝐬! 💡 Learn directly from industry leaders at Microsoft and LinkedIn Learning and gain in-demand skills to elevate your career—all without spending a dime! 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/41ODJMi 📈 Don’t miss this chance to build your skills, earn certifications, and get job-ready—all for free. Your journey in data analytics begins now! 🔗 Start Learning Today!

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Complete Roadmap to become a data scientist in 5 months Free Resources to learn Data Science: https://t.me/datasciencefun Week 1-2: Fundamentals - Day 1-3: Introduction to Data Science, its applications, and roles. - Day 4-7: Brush up on Python programming. - Day 8-10: Learn basic statistics and probability. Week 3-4: Data Manipulation and Visualization - Day 11-15: Pandas for data manipulation. - Day 16-20: Data visualization with Matplotlib and Seaborn. Week 5-6: Machine Learning Foundations - Day 21-25: Introduction to scikit-learn. - Day 26-30: Linear regression and logistic regression. Work on Data Science Projects: https://t.me/pythonspecialist/29 Week 7-8: Advanced Machine Learning - Day 31-35: Decision trees and random forests. - Day 36-40: Clustering (K-Means, DBSCAN) and dimensionality reduction. Week 9-10: Deep Learning - Day 41-45: Basics of Neural Networks and TensorFlow/Keras. - Day 46-50: Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). Week 11-12: Data Engineering - Day 51-55: Learn about SQL and databases. - Day 56-60: Data preprocessing and cleaning. Week 13-14: Model Evaluation and Optimization - Day 61-65: Cross-validation, hyperparameter tuning. - Day 66-70: Evaluation metrics (accuracy, precision, recall, F1-score). Week 15-16: Big Data and Tools - Day 71-75: Introduction to big data technologies (Hadoop, Spark). - Day 76-80: Basics of cloud computing (AWS, GCP, Azure). Week 17-18: Deployment and Production - Day 81-85: Model deployment with Flask or FastAPI. - Day 86-90: Containerization with Docker, cloud deployment (AWS, Heroku). Week 19-20: Specialization - Day 91-95: NLP or Computer Vision, based on your interests. Week 21-22: Projects and Portfolios - Day 96-100: Work on personal data science projects. Week 23-24: Soft Skills and Networking - Day 101-105: Improve communication and presentation skills. - Day 106-110: Attend online data science meetups or forums. Week 25-26: Interview Preparation - Day 111-115: Practice coding interviews on platforms like LeetCode. - Day 116-120: Review your projects and be ready to discuss them. Week 27-28: Apply for Jobs - Day 121-125: Start applying for entry-level data scientist positions. Week 29-30: Interviews - Day 126-130: Attend interviews, practice whiteboard problems. Week 31-32: Continuous Learning - Day 131-135: Stay updated with the latest trends in data science. Week 33-34: Accepting Offers - Day 136-140: Evaluate job offers and negotiate if necessary. Week 35-36: Settling In - Day 141-150: Start your new data science job, adapt to the team, and continue learning on the job. ENJOY LEARNING 👍👍

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𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐉𝐨𝐛𝐬 𝐈𝐧 𝐓𝐨𝐩 𝐂𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 😍 Companies Hiring:- - Capgemini - Wipro - S&P Global - Infosys - Cognizant Expected Salary:- 8 To 24 LPA Job Location:- Across India 𝐀𝐩𝐩𝐥𝐲 𝐋𝐢𝐧𝐤👇:- https://bit.ly/3ZGZMS9 Complete the registration process Select company name & role

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Pandas for Data Science

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𝐀𝐈 & 𝐌𝐋 𝐅𝐑𝐄𝐄 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐮𝐫𝐬𝐞𝐬 𝐅𝐫𝐨𝐦 𝐓𝐨𝐩 𝐈𝐧𝐬𝐭𝐢𝐭𝐮𝐭𝐢𝐨𝐧𝐬!😍 Explore these 6 amazing courses offered by the Government of India, Google, Harvard, MIT, and IBM. Gain hands-on knowledge in Generative AI, Python, Machine Learning, and AI’s impact on business strategy—all at no cost. Plus, you’ll earn certificates to boost your resume! 𝐋𝐢𝐧𝐤 👇:- https://bit.ly/3ZZj9rc Enroll For FREE & Get Certified 🎓

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Repost from Free Courses with Certificate - Python Programming, Data Science, Java Coding, SQL, Web Development, AI, ML, ChatGPT Expert

In every family tree, there is 1 person who breaks out the middle-class chain and works hard to become a millionaire and changes the lives of everyone forever. May that be you in 2025. Happy New Year!

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Data Structure in Python

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What's the most significant achievement you accomplished in 2024, and what's the target for 2025?

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𝐈𝐧𝐟𝐨𝐬𝐲𝐬 𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐬𝐭 𝐇𝐢𝐫𝐢𝐧𝐠 𝐃𝐫𝐢𝐯𝐞😍 Office Location:- Bangalore Role:- Data Analyst Qualification:- MCA,MTech,MBA,BTech,BCA,Bachelor of Engineering Expected Salary:- 10 To 25LPA 𝐀𝐩𝐩𝐥𝐲 𝐧𝐨𝐰👇:- https://pdlink.in/41QGJYs Apply before the link expires

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