اکنون در دسترس! پژوهش تلگرام ۲۰۲۵ — مهمترین بینشهای سال 
Data Science & Machine Learning
رفتن به کانال در Telegram
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
نمایش بیشتر📈 تحلیل کانال تلگرام Data Science & Machine Learning
کانال Data Science & Machine Learning (@datasciencefun) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 75 645 مشترک است و جایگاه 2 114 را در دسته آموزش و رتبه 4 359 را در منطقه الهند دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 75 645 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 11 ژوئن, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر 911 و در ۲۴ ساعت گذشته برابر 29 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 3.63% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 1.36% واکنش نسبت به کل مشترکان کسب میکند.
- دسترسی پستها: هر پست به طور میانگین 2 747 بازدید دریافت میکند. در اولین روز معمولاً 1 032 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 5 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند learning, accuracy, distribution, panda, dataset تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاههای شخصی توصیف میکند:
“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”
به لطف بهروزرسانیهای پرتکرار (آخرین داده در تاریخ 12 ژوئن, 2026)، کانال همواره بهروز و دارای دسترسی بالاست. تحلیلها نشان میدهد مخاطبان بهطور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته آموزش تبدیل کردهاند.
75 645
مشترکین
+2924 ساعت
+2107 روز
+91130 روز
آرشیو پست ها
Which library is used for basic plotting in Python?
𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀, 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝘄𝗶𝘁𝗵 𝗔𝗜 𝗮𝗿𝗲 𝗵𝗶𝗴𝗵𝗹𝘆 𝗱𝗲𝗺𝗮𝗻𝗱𝗶𝗻𝗴 𝗶𝗻 𝟮𝟬𝟮𝟲😍
Learn Data Science and AI Taught by Top Tech professionals
60+ Hiring Drives Every Month
𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝗲𝘀:-
- 12.65 Lakhs Highest Salary
- 500+ Partner Companies
- 100% Job Assistance
- 5.7 LPA Average Salary
𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗡𝗼𝘄👇:-
Online :- https://pdlink.in/4fdWxJB
🔹 Hyderabad :- https://pdlink.in/4kFhjn3
🔹 Pune:- https://pdlink.in/45p4GrC
🔹 Noida :- https://linkpd.in/DaNoida
Hurry Up 🏃♂️! Limited seats are available.
✅ Data Science Interview Prep Guide 📊🧠
Whether you're a fresher or career-switcher, here’s how to prep step-by-step:
1️⃣ Understand the Role
Data scientists solve problems using data. Core responsibilities:
• Data cleaning & analysis
• Building predictive models
• Communicating insights
• Working with business/product teams
2️⃣ Core Skills Needed
✔️ Python (NumPy, Pandas, Matplotlib, Scikit-learn)
✔️ SQL
✔️ Statistics & probability
✔️ Machine Learning basics
✔️ Data storytelling & visualization (Power BI / Tableau / Seaborn)
3️⃣ Key Interview Areas
A. Python & Coding
• Write code to clean and analyze data
• Solve logic problems (e.g., reverse a list, group data by key)
• List vs Dict vs DataFrame usage
B. Statistics & Probability
• Hypothesis testing
• p-values, confidence intervals
• Normal distribution, sampling
C. Machine Learning Concepts
• Supervised vs unsupervised learning
• Overfitting, regularization, cross-validation
• Algorithms: Linear Regression, Decision Trees, KNN, SVM
D. SQL
• Joins, GROUP BY, subqueries
• Window functions
• Data aggregation and filtering
E. Business & Communication
• Explain model results to non-tech stakeholders
• What metrics would you track for [business case]?
• Tell me about a time you used data to influence a decision
4️⃣ Build Your Portfolio
✅ Do projects like:
• E-commerce sales analysis
• Customer churn prediction
• Movie recommendation system
✅ Host on GitHub or Kaggle
✅ Add visual dashboards and insights
5️⃣ Practice Platforms
• LeetCode (SQL, Python)
• HackerRank
• StrataScratch (SQL case studies)
• Kaggle (competitions & notebooks)
💬 Tap ❤️ for more!
𝗧𝗼𝗽 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝘁𝗼 𝗟𝗮𝗻𝗱 𝗮 𝗛𝗶𝗴𝗵-𝗣𝗮𝘆𝗶𝗻𝗴 𝗝𝗼𝗯 𝗶𝗻 𝟮𝟬𝟮𝟲🔥
Learn from scratch → Build real projects → Get placed
✅ 2000+ Students Already Placed
🤝 500+ Hiring Partners
💼 Avg Salary: ₹7.4 LPA
🚀 Highest Package: ₹41 LPA
Fullstack :- https://pdlink.in/4hO7rWY
Data Analytics :- https://pdlink.in/4fdWxJB
📈 Don’t just scroll… Start today & secure your 2026 job NOW
Which library is used for advanced and attractive visualizations?
What type of chart is best for showing trends over time?
Which library is used for basic plotting in Python?
Freshers are getting paid 10 - 15 Lakhs by learning AI & ML skill
📢 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗔𝗹𝗲𝗿𝘁 – 𝗔𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗮𝗻𝗱 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴
Open for all. No Coding Background Required
📊 Learn AI/ML from Scratch
🤖 AI Tools & Automation
📈 Build real world Projects for job ready portfolio
🎓 Vishlesan i-Hub, IIT Patna Certification Program
🔥Deadline :- 12th April
𝗔𝗽𝗽𝗹𝘆 𝗡𝗼𝘄👇 :-
https://pdlink.in/41ZttiU
.
Get Placement Assistance With 5000+ Companies from Masai School
🔥2026 New IT Certification Prep Kit – Free!
SPOTO cover: #Python #AI #Cisco #PMI #Fortinet #AWS #Azure #Excel #CompTIA #ITIL #Cloud + more
✅ Grab yours free kit now:
• Free Courses (Python, Excel, Cyber Security, Cisco, SQL, ITIL, PMP, AWS)
👉 https://bit.ly/4tBOrAn
• IT Certs E-book(Cisco, PMI, huawei, ccna/ccnp, ISACA, Microsoft, CompTIA)
👉https://bit.ly/4spTJOu
• IT Exams Skill Test
👉 https://bit.ly/4taBZrp
• Free AI Materials & Support Tools
👉 https://bit.ly/4snzUaq
• Free Cloud Study Guide
👉 https://bit.ly/4mfFVo4
💬 Need exam help? Contact admin: wa.link/pdioe4
✅ Join our IT community: get free study materials, exam tips & peer support
https://chat.whatsapp.com/BiazIVo5RxfKENBv10F444
✅ Data Cleaning in Pandas 🐍🧹
👉 In real projects, 80% of the work = Data Cleaning
Because raw data is always messy 😅
🔹 1. Why Data Cleaning?
Real-world data may have:
❌ Missing values
❌ Duplicate records
❌ Wrong formats
❌ Extra spaces
👉 Cleaning makes data usable for analysis & ML.
🔥 2. Handling Missing Values
✅ Check Missing Values
df.isnull()
df.isnull().sum()
✅ Remove Missing Values
df.dropna()
✅ Fill Missing Values
df.fillna(0)
👉 Replace missing values with 0 or mean.
🔹 3. Remove Duplicates
df.drop_duplicates()
🔹 4. Rename Columns
df.rename(columns={"Name": "Full_Name"}, inplace=True)
🔹 5. Change Data Types
df["Age"] = df["Age"].astype(int)
🔹 6. Remove Extra Spaces
df["Name"] = df["Name"].str.strip()
🔹 7. Replace Values
df["City"] = df["City"].replace("NY", "New York")
🔹 8. Why This is Important?
✔ Clean data = better insights
✔ Clean data = better ML models
✔ Used in every real-world project
🎯 Today’s Goal
✔ Handle missing values
✔ Remove duplicates
✔ Fix data types
✔ Clean text data
👉 Double Tap ❤️ For More
Useful AI channels on WhatsApp 🤖
Artificial Intelligence: https://whatsapp.com/channel/0029VbBDFBI9Gv7NCbFdkg36
Python Programming: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L
AI Tricks: https://whatsapp.com/channel/0029Vb6xxJGGk1FnoCYE660N
AI Discovery: https://whatsapp.com/channel/0029VbBHlc7H5JLuv8L9d72T
AI Magic: https://whatsapp.com/channel/0029VbBA1z1JuyAH7BNeT43b
OpenAI: https://whatsapp.com/channel/0029VbAbfqcLtOj7Zen5tt3o
Tech News: https://whatsapp.com/channel/0029VbBo9qY1t90emAy5P62s
ChatGPT for Education: https://whatsapp.com/channel/0029Vb6r21H9hXFFoxvWR32C
ChatGPT Tips: https://whatsapp.com/channel/0029Vb6ZoSzBA1f3paReKB3B
AI for Leaders: https://whatsapp.com/channel/0029VbB9LO872WTwyqNlB63R
AI For Business: https://whatsapp.com/channel/0029VbBn5bn0rGiLOhM3vi1v
AI For Teachers: https://whatsapp.com/channel/0029Vb7LGgLCRs1mp86TH614
How to AI: https://whatsapp.com/channel/0029VbBHQZM7z4khHBTVtI0Q
AI For Students: https://whatsapp.com/channel/0029VbBIV47I7Be9BZMAJq3s
Copilot: https://whatsapp.com/channel/0029VbAW0QBDOQIgYcbwBd1l
Generative AI: https://whatsapp.com/channel/0029VazaRBY2UPBNj1aCrN0U
ChatGPT: https://whatsapp.com/channel/0029Vb6R8PI6WaKwRzLKKI0r
Deepseek: https://whatsapp.com/channel/0029Vb9js9sGpLHJGIvX5g1w
Finance & AI: https://whatsapp.com/channel/0029Vax0HTt7Noa40kNI2B1P
Google Facts: https://whatsapp.com/channel/0029VbBnkGm6LwHriVjB5I04
Perplexity AI: https://whatsapp.com/channel/0029VbAa05yISTkGgBqyC00U
Grok AI: https://whatsapp.com/channel/0029VbAU3pWChq6T5bZxUk1r
Deeplearning AI: https://whatsapp.com/channel/0029VbAKiI1FSAt81kV3lA0t
AI Discovery: https://whatsapp.com/channel/0029VbBHlc7H5JLuv8L9d72T
AI News: https://whatsapp.com/channel/0029VbAWNue1iUxjLo2DFx2U
Machine Learning: https://whatsapp.com/channel/0029VawtYcJ1iUxcMQoEuP0O
Jobs: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
Double Tap ❤️ for more
𝗦𝗯𝗲𝗿𝟱𝟬𝟬 𝗕𝗮𝘁𝗰𝗵 𝟳 — 𝗙𝗿𝗲𝗲 𝗔𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗼𝗿 𝗳𝗼𝗿 𝗔𝗜 & 𝗗𝗲𝗲𝗽𝗧𝗲𝗰𝗵 𝗦𝘁𝗮𝗿𝘁𝘂𝗽𝘀 🚀
Ready to scale your startup beyond local market?
Who should apply:
✅ Startups with MVP and early traction
✅ DeepTech: GenAI, robotics, advanced materials, photonics, quantum computing
✅ Applied AI for research, Earth remote sensing, autonomous transport
✅ International founders exploring the Russian market
What you'll get:
📍 12-week online program in English
📍 International mentors (Europe, US, Asia, Middle East)
📍 Access to investors & corporate customers
📍 Demo Day at Moscow Startup Summit (Fall 2026)
Results:
📈 Revenue grows 4x on average, up to 1,000x for some teams
🤝 10,900+ contracts and pilots with corporations (6 seasons)
Program stages:
1️⃣ Online bootcamp for 150 teams
2️⃣ 25 best teams → intensive mentorship
3️⃣ Demo Day presentation
Key details:
📅 Deadline: 10 April 2026
💰 Participation: Free of charge
🌐 Format: Online
💬 Language: English
𝗔𝗽𝗽𝗹𝘆 𝗡𝗼𝘄 👇
https://sberbank-500.ru/
💥 Don't wait. Scale your startup with Sber500.
React ❤️ for more startup opportunities!
#DataScience #MachineLearning #DeepTech #GenAI #Startup #Accelerator #AI
📊 Python for Data Science – Complete Beginner Roadmap 🐍🚀
🔹 What is Data Science?
Data Science is about: Collecting data Cleaning it Analyzing it Finding insights Making predictions
👉 Example:
- Predict sales 📈
- Analyze customer behavior 🛒
- Detect fraud 💳
🧭 Step-by-Step Roadmap
🔹 1️⃣ Strengthen Python Basics
Focus on: Lists, dictionaries Loops & conditions Functions Basic file handling
👉 Because data is handled using these structures.
🔹 2️⃣ Learn NumPy (Numerical Computing)
NumPy is used for: Fast calculations Working with arrays
import numpy as np
arr = np.array([1,2,3])
print(arr.mean())
👉 Used in: Machine learning Scientific computing
🔹 3️⃣ Learn Pandas (Most Important 🔥)
Pandas helps you: Read data (CSV, Excel) Clean data Analyze data
import pandas as pd
df = pd.read_csv("data.csv")
print(df.head())
👉 Must learn: head(), info() filtering groupby() merge()
🔹 4️⃣ Data Visualization
Tools: matplotlib seaborn
import matplotlib.pyplot as plt
plt.plot([1,2,3],[10,20,30])
plt.show()
👉 Used to: Present insights Create reports Build dashboards
🔹 5️⃣ Statistics Basics (Very Important)
Learn: Mean, Median, Mode Standard Deviation Probability basics
👉 Data science = math + logic + code
🔹 6️⃣ Data Cleaning (Real-World Skill)
Real data is messy 😅
You should learn:
- Handling missing values
- Removing duplicates
- Fixing data types
df.dropna()
df.fillna(0)
🔹 7️⃣ Intro to Machine Learning
Using scikit-learn:
from sklearn.linear_model import LinearRegression
Learn:
- Regression
- Classification
- Model training
🔹 8️⃣ Real Projects (Most Important 🚀)
Start building:
💡 Project Ideas:
- Sales analysis dashboard
- IPL data analysis
- Netflix dataset insights
- Customer churn prediction
🧠 Double Tap ❤️ For More
Learn Ai in 2026 —Absolutely FREE!🚀
💸 Cost: ~₹10,000~ ₹0 (FREE!)
What you’ll learn:
✅ 25+ Powerful AI Tools
✅ Crack Interviews with Ai
✅ Build Websites in seconds
✅ Make Videos PPT
Enroll Now (free): https://tinyurl.com/Free-Ai-Course-a
⚠️ Register Get Ai Certificate for resume
10 Simple Habits to Boost Your Data Science Skills 🧠📊
1) Practice data wrangling daily (Pandas, dplyr)
2) Work on small end-to-end projects (ETL, analysis, visualization)
3) Revisit and improve previous notebooks or scripts
4) Share findings in a clear, story-driven way
5) Follow data science blogs, newsletters, and researchers
6) Tackle weekly datasets or Kaggle competitions
7) Maintain a notebooks/journal with experiments and results
8) Version control your work (Git + GitHub)
9) Learn to communicate uncertainty (confidence intervals, p-values)
10) Stay curious about new tools (SQL, Python libs, ML basics)
💬 React "❤️" for more! 😊
𝗣𝗮𝘆 𝗔𝗳𝘁𝗲𝗿 𝗣𝗹𝗮𝗰𝗲𝗺𝗲𝗻𝘁 - 𝗟𝗲𝗮𝗿𝗻 𝗖𝗼𝗱𝗶𝗻𝗴 𝗙𝗿𝗼𝗺 𝗜𝗜𝗧 𝗔𝗹𝘂𝗺𝗻𝗶🔥
💻 Learn Frontend + Backend from scratch
📂 Build Real Projects (Portfolio Ready)
🌟 2000+ Students Placed
🤝 500+ Hiring Partners
💼 Avg. Rs. 7.4 LPA
🚀 41 LPA Highest Package
📈 Skills = Opportunities = High Salary
𝗔𝗽𝗽𝗹𝘆 𝗡𝗼𝘄👇:-
https://pdlink.in/4hO7rWY
💥 Stop scrolling. Start building yourTech career
