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Loading CSV files into a database using Python.
#python #csv #dataAnalysis
⭐️ BEST DATA SCIENCE CHANNELS ON TELEGRAM ⭐️
#python #csv #dataAnalysis
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SciPy.pdf
206.4 KB
Unlock the full power of SciPy with my comprehensive cheat sheet!
Master essential functions for:
Function optimization and solving equations
Linear algebra operations
ODE integration and statistical analysis
Signal processing and spatial data manipulation
Data clustering and distance computation ...and much more!
💯 BEST DATA SCIENCE CHANNELS ON TELEGRAM 🌟
Master essential functions for:
Function optimization and solving equations
Linear algebra operations
ODE integration and statistical analysis
Signal processing and spatial data manipulation
Data clustering and distance computation ...and much more!
#Python #SciPy #MachineLearning #DataScience #CheatSheet #ArtificialIntelligence #Optimization #LinearAlgebra #SignalProcessing #BigData
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Four best-advanced university courses on NLP & LLM to advance your skills:
1. Advanced NLP -- Carnegie Mellon University
Link: https://lnkd.in/ddEtMghr
2. Recent Advances on Foundation Models -- University of Waterloo
Link: https://lnkd.in/dbdpUV9v
3. Large Language Model Agents -- University of California, Berkeley
Link: https://lnkd.in/d-MdSM8Y
4. Advanced LLM Agent -- University Berkeley
Link: https://lnkd.in/dvCD4HR4
#LLM #python #AI #Agents #RAG #NLP
💯 BEST DATA SCIENCE CHANNELS ON TELEGRAM 🌟
1. Advanced NLP -- Carnegie Mellon University
Link: https://lnkd.in/ddEtMghr
2. Recent Advances on Foundation Models -- University of Waterloo
Link: https://lnkd.in/dbdpUV9v
3. Large Language Model Agents -- University of California, Berkeley
Link: https://lnkd.in/d-MdSM8Y
4. Advanced LLM Agent -- University Berkeley
Link: https://lnkd.in/dvCD4HR4
#LLM #python #AI #Agents #RAG #NLP
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Top 100+ questions%0A %22Google Data Science Interview%22.pdf
16.7 MB
Google is known for its rigorous data science interview process, which typically follows a hybrid format. Candidates are expected to demonstrate strong programming skills, solid knowledge in statistics and machine learning, and a keen ability to approach problems from a product-oriented perspective.
To succeed, one must be proficient in several critical areas: statistics and probability, SQL and Python programming, product sense, and case study-based analytics.
This curated list features over 100 of the most commonly asked and important questions in Google data science interviews. It serves as a comprehensive resource to help candidates prepare effectively and confidently for the challenge ahead.
#DataScience #GoogleInterview #InterviewPrep #MachineLearning #SQL #Statistics #ProductAnalytics #Python #CareerGrowth
https://t.me/addlist/0f6vfFbEMdAwODBk
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@CodeProgrammer Matplotlib.pdf
4.3 MB
The Complete Visual Guide for Data Enthusiasts
Matplotlib is a powerful Python library for data visualization, essential not only for acing job interviews but also for building a solid foundation in analytical thinking and data storytelling.
This step-by-step tutorial guide walks learners through everything from the basics to advanced techniques in Matplotlib. It also includes a curated collection of the most frequently asked Matplotlib-related interview questions, making it an ideal resource for both beginners and experienced professionals.
#Matplotlib #DataVisualization #Python #DataScience #InterviewPrep #Analytics #TechCareer #LearnToCode
https://t.me/addlist/0f6vfFbEMdAwODBk
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@codeprogrammer machine learning notes.pdf
21 MB
Best Machine Learning Notes
Join to our WhatsApp📱 channel:
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Join to our WhatsApp
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9 machine learning concepts for ML engineers!
(explained as visually as possible)
Here's a recap of several visual summaries posted in the Daily Dose of Data Science newsletter.
1️⃣ 4 strategies for Multi-GPU Training.
- Training at scale? Learn these strategies to maximize efficiency and minimize model training time.
- Read here: https://lnkd.in/gmXF_PgZ
2️⃣ 4 ways to test models in production
- While testing a model in production might sound risky, ML teams do it all the time, and it isn’t that complicated.
- Implemented here: https://lnkd.in/g33mASMM
3️⃣ Training & inference time complexity of 10 ML algorithms
Understanding the run time of ML algorithms is important because it helps you:
- Build a core understanding of an algorithm.
- Understand the data-specific conditions to use the algorithm
- Read here: https://lnkd.in/gKJwJ__m
4️⃣ Regression & Classification Loss Functions.
- Get a quick overview of the most important loss functions and when to use them.
- Read here: https://lnkd.in/gzFPBh-H
5️⃣ Transfer Learning, Fine-tuning, Multitask Learning, and Federated Learning.
- The holy grail of advanced learning paradigms, explained visually.
- Learn about them here: https://lnkd.in/g2hm8TMT
6️⃣ 15 Pandas to Polars to SQL to PySpark Translations.
- The visual will help you build familiarity with four popular frameworks for data analysis and processing.
- Read here: https://lnkd.in/gP-cqjND
7️⃣ 11 most important plots in data science
- A must-have visual guide to interpret and communicate your data effectively.
- Explained here: https://lnkd.in/geMt98tF
8️⃣ 11 types of variables in a dataset
Understand and categorize dataset variables for better feature engineering.
- Explained here: https://lnkd.in/gQxMhb_p
9️⃣ NumPy cheat sheet for data scientists
- The ultimate cheat sheet for fast, efficient numerical computing in Python.
- Read here: https://lnkd.in/gbF7cJJE
🔗 Our Telegram channels: https://t.me/addlist/0f6vfFbEMdAwODBk
📱 Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
(explained as visually as possible)
Here's a recap of several visual summaries posted in the Daily Dose of Data Science newsletter.
- Training at scale? Learn these strategies to maximize efficiency and minimize model training time.
- Read here: https://lnkd.in/gmXF_PgZ
- While testing a model in production might sound risky, ML teams do it all the time, and it isn’t that complicated.
- Implemented here: https://lnkd.in/g33mASMM
Understanding the run time of ML algorithms is important because it helps you:
- Build a core understanding of an algorithm.
- Understand the data-specific conditions to use the algorithm
- Read here: https://lnkd.in/gKJwJ__m
- Get a quick overview of the most important loss functions and when to use them.
- Read here: https://lnkd.in/gzFPBh-H
- The holy grail of advanced learning paradigms, explained visually.
- Learn about them here: https://lnkd.in/g2hm8TMT
- The visual will help you build familiarity with four popular frameworks for data analysis and processing.
- Read here: https://lnkd.in/gP-cqjND
- A must-have visual guide to interpret and communicate your data effectively.
- Explained here: https://lnkd.in/geMt98tF
Understand and categorize dataset variables for better feature engineering.
- Explained here: https://lnkd.in/gQxMhb_p
- The ultimate cheat sheet for fast, efficient numerical computing in Python.
- Read here: https://lnkd.in/gbF7cJJE
#MachineLearning #DataScience #MLEngineering #DeepLearning #AI #MLOps #BigData #Python #NumPy #Pandas #Visualization
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A new interactive sentiment visualization project has been developed, featuring a dynamic smiley face that reflects sentiment analysis results in real time. Using a natural language processing model, the system evaluates input text and adjusts the smiley face expression accordingly:
🙂 Positive sentiment
☹️ Negative sentiment
The visualization offers an intuitive and engaging way to observe sentiment dynamics as they happen.
🔗 GitHub: https://lnkd.in/e_gk3hfe
📰 Article: https://lnkd.in/e_baNJd2
#AI #SentimentAnalysis #DataVisualization #InteractiveDesign #NLP #MachineLearning #Python #GitHubProjects #TowardsDataScience
🔗 Our Telegram channels: https://t.me/addlist/0f6vfFbEMdAwODBk
📱 Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
The visualization offers an intuitive and engaging way to observe sentiment dynamics as they happen.
#AI #SentimentAnalysis #DataVisualization #InteractiveDesign #NLP #MachineLearning #Python #GitHubProjects #TowardsDataScience
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Python Cheat Sheet
⚡️ Our Telegram channels: https://t.me/addlist/0f6vfFbEMdAwODBk
📱 Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
#AI #SentimentAnalysis #DataVisualization #pandas #Numpy #InteractiveDesign #NLP #MachineLearning #Python #GitHubProjects #TowardsDataScience
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from SQL to pandas.pdf
1.3 MB
#DataScience #SQL #pandas #InterviewPrep #Python #DataAnalysis #CareerGrowth #TechTips #Analytics
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Numpy from basics to advanced.pdf
2.4 MB
NumPy is an essential library in the world of data science, widely recognized for its efficiency in numerical computations and data manipulation. This powerful tool simplifies complex operations with arrays, offering a faster and cleaner alternative to traditional Python lists and loops.
The "Mastering NumPy" booklet provides a comprehensive walkthrough—from array creation and indexing to mathematical/statistical operations and advanced topics like reshaping and stacking. All concepts are illustrated with clear, beginner-friendly examples, making it ideal for anyone aiming to boost their data handling skills.
#NumPy #Python #DataScience #MachineLearning #AI #BigData #DeepLearning #DataAnalysis
✉️ Our Telegram channels: https://t.me/addlist/0f6vfFbEMdAwODBk📱 Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
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🚀 DataCamp has officially partnered with Polars**—a cutting-edge DataFrame library designed for speed and efficiency!
To mark this exciting collaboration, **DataCamp is offering free access to its brand-new course *“Introduction to Polars”* for the next 90 days. 🎉
This course is a great opportunity for learners and professionals alike to master data cleaning, transformation, and analysis with Polars' high-performance engine, lazy execution, and powerful groupby operations.
Unlock the full potential of data workflows and explore how Polars can supercharge large-scale data processing.
🔗 Start learning now:
https://www.datacamp.com/courses/introduction-to-polars
🌟 Join the communities:
To mark this exciting collaboration, **DataCamp is offering free access to its brand-new course *“Introduction to Polars”* for the next 90 days. 🎉
This course is a great opportunity for learners and professionals alike to master data cleaning, transformation, and analysis with Polars' high-performance engine, lazy execution, and powerful groupby operations.
Unlock the full potential of data workflows and explore how Polars can supercharge large-scale data processing.
🔗 Start learning now:
https://www.datacamp.com/courses/introduction-to-polars
#DataScience #Polars #Python #BigData #DataEngineering #MachineLearning #DataAnalytics #OpenSource #DataCamp #FreeCourse #LearnDataScience
✉️ Our Telegram channels: https://t.me/addlist/0f6vfFbEMdAwODBk📱 Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
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python_basics.pdf
212.3 KB
I've just compiled a set of clean and powerful Python Cheat Sheets to help beginners and intermediates speed up their coding workflow.
Whether you're brushing up on the basics or diving into data science, these sheets will save you time and boost your productivity.
Python Basics
Jupyter Notebook Tips
Importing Libraries
NumPy Essentials
Pandas Overview
Perfect for students, developers, and anyone looking to keep essential Python knowledge at their fingertips.
#Python #CheatSheets #PythonTips #DataScience #JupyterNotebook #NumPy #Pandas #MachineLearning #AI #CodingTips #PythonForBeginners
✉️ Our Telegram channels: https://t.me/addlist/0f6vfFbEMdAwODBk📱 Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
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#DataScience #HowToBecomeADataScientist #ML2025 #Python #SQL #MachineLearning #MathForDataScience #BigData #MLOps #DeepLearning #AIResearch #DataVisualization #PortfolioProjects #CloudComputing #DSCareerPath
✉️ Our Telegram channels: https://t.me/addlist/0f6vfFbEMdAwODBk📱 Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
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𝗬𝗼𝘂𝗿_𝗗𝗮𝘁𝗮_𝗦𝗰𝗶𝗲𝗻𝗰𝗲_𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄_𝗦𝘁𝘂𝗱𝘆_𝗣𝗹𝗮𝗻.pdf
7.7 MB
1. Master the fundamentals of Statistics
Understand probability, distributions, and hypothesis testing
Differentiate between descriptive vs inferential statistics
Learn various sampling techniques
2. Get hands-on with Python & SQL
Work with data structures, pandas, numpy, and matplotlib
Practice writing optimized SQL queries
Master joins, filters, groupings, and window functions
3. Build real-world projects
Construct end-to-end data pipelines
Develop predictive models with machine learning
Create business-focused dashboards
4. Practice case study interviews
Learn to break down ambiguous business problems
Ask clarifying questions to gather requirements
Think aloud and structure your answers logically
5. Mock interviews with feedback
Use platforms like Pramp or connect with peers
Record and review your answers for improvement
Gather feedback on your explanation and presence
6. Revise machine learning concepts
Understand supervised vs unsupervised learning
Grasp overfitting, underfitting, and bias-variance tradeoff
Know how to evaluate models (precision, recall, F1-score, AUC, etc.)
7. Brush up on system design (if applicable)
Learn how to design scalable data pipelines
Compare real-time vs batch processing
Familiarize with tools: Apache Spark, Kafka, Airflow
8. Strengthen storytelling with data
Apply the STAR method in behavioral questions
Simplify complex technical topics
Emphasize business impact and insight-driven decisions
9. Customize your resume and portfolio
Tailor your resume for each job role
Include links to projects or GitHub profiles
Match your skills to job descriptions
10. Stay consistent and track progress
Set clear weekly goals
Monitor covered topics and completed tasks
Reflect regularly and adapt your plan as needed
#DataScience #InterviewPrep #MLInterviews #DataEngineering #SQL #Python #Statistics #MachineLearning #DataStorytelling #SystemDesign #CareerGrowth #DataScienceRoadmap #PortfolioBuilding #MockInterviews #JobHuntingTips
✉️ Our Telegram channels: https://t.me/addlist/0f6vfFbEMdAwODBk📱 Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
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🚀 FREE IT Study Kits for 2025 — Grab Yours Now!
Just found these zero-cost resources from SPOTO👇
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🧠 Skill Test (Free!): https://bit.ly/3PoKH39
Tag a friend & level up together 💪
🌐 Join the IT Study Group: https://chat.whatsapp.com/E3Vkxa19HPO9ZVkWslBO8s
📲 1-on-1 Exam Help: https://wa.link/k0vy3x
👑Last 24 HOURS to grab Mid-Year Mega Sale prices！Don’t miss Lucky Draw👇
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Just found these zero-cost resources from SPOTO👇
Perfect if you're prepping for #Cisco, #AWS, #PMP, #AI, #Python, #Excel, or #Cybersecurity!
✅ 100% Free
✅ No signup traps
✅ Instantly downloadable
📘 IT Certs E-book: https://bit.ly/4fJSoLP
☁️ Cloud & AI Kits: https://bit.ly/3F3lc5B
📊 Cybersecurity, Python & Excel: https://bit.ly/4mFrA4g
🧠 Skill Test (Free!): https://bit.ly/3PoKH39
Tag a friend & level up together 💪
🌐 Join the IT Study Group: https://chat.whatsapp.com/E3Vkxa19HPO9ZVkWslBO8s
📲 1-on-1 Exam Help: https://wa.link/k0vy3x
👑Last 24 HOURS to grab Mid-Year Mega Sale prices！Don’t miss Lucky Draw👇
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🐍📰 This tutorial will give you an overview of LangGraph fundamentals through hands-on examples, and the tools needed to build your own LLM workflows and agents in LangGraph
Link: https://realpython.com/langgraph-python/
Link: https://realpython.com/langgraph-python/
#LangGraph #Python #LLMWorkflows #AIAgents #RealPython #PythonTutorials #LargeLanguageModels #AIAgents #WorkflowAutomation #PythonForA
✉️ Our Telegram channels: https://t.me/addlist/0f6vfFbEMdAwODBk📱 Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
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