👨🏻💻 If you are looking for datasets to do financial projects, the datasets presented on the Kaggle site can be a great option.
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11 types of variables in a Dataset
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📂 Tags: #datasets #Python #ML
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Datasets Guide 📚
A practical and beginner-friendly guide that walks you through everything you need to know about datasets in machine learning and deep learning. This guide explains how to load, preprocess, and use datasets effectively for training models. It's an essential resource for anyone working with LLMs or custom training workflows, especially with tools like Unsloth.
Importance:
Understanding how to properly handle datasets is a critical step in building accurate and efficient AI models. This guide simplifies the process, helping you avoid common pitfalls and optimize your data pipeline for better performance.
Link: https://docs.unsloth.ai/basics/datasets-guide
#MachineLearning #DeepLearning #Datasets #DataScience #AI #Unsloth #LLM #TrainingData #MLGuide
⚡️ BEST DATA SCIENCE CHANNELS ON TELEGRAM 🌟
A practical and beginner-friendly guide that walks you through everything you need to know about datasets in machine learning and deep learning. This guide explains how to load, preprocess, and use datasets effectively for training models. It's an essential resource for anyone working with LLMs or custom training workflows, especially with tools like Unsloth.
Importance:
Understanding how to properly handle datasets is a critical step in building accurate and efficient AI models. This guide simplifies the process, helping you avoid common pitfalls and optimize your data pipeline for better performance.
Link: https://docs.unsloth.ai/basics/datasets-guide
#MachineLearning #DeepLearning #Datasets #DataScience #AI #Unsloth #LLM #TrainingData #MLGuide
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Topic: Handling Datasets of All Types – Part 1 of 5: Introduction and Basic Concepts
---
1. What is a Dataset?
• A dataset is a structured collection of data, usually organized in rows and columns, used for analysis or training machine learning models.
---
2. Types of Datasets
• Structured Data: Tables, spreadsheets with rows and columns (e.g., CSV, Excel).
• Unstructured Data: Images, text, audio, video.
• Semi-structured Data: JSON, XML files containing hierarchical data.
---
3. Common Dataset Formats
• CSV (Comma-Separated Values)
• Excel (.xls, .xlsx)
• JSON (JavaScript Object Notation)
• XML (eXtensible Markup Language)
• Images (JPEG, PNG, TIFF)
• Audio (WAV, MP3)
---
4. Loading Datasets in Python
• Use libraries like
• Use libraries like
---
5. Basic Dataset Exploration
• Check shape and size:
• Preview data:
• Check for missing values:
---
6. Summary
• Understanding dataset types is crucial before processing.
• Loading and exploring datasets helps identify cleaning and preprocessing needs.
---
Exercise
• Load a CSV and JSON dataset in Python, print their shapes, and identify missing values.
---
#DataScience #Datasets #DataLoading #Python #DataExploration
The rest of the parts👇
https://xn--r1a.website/DataScienceM🌟
---
1. What is a Dataset?
• A dataset is a structured collection of data, usually organized in rows and columns, used for analysis or training machine learning models.
---
2. Types of Datasets
• Structured Data: Tables, spreadsheets with rows and columns (e.g., CSV, Excel).
• Unstructured Data: Images, text, audio, video.
• Semi-structured Data: JSON, XML files containing hierarchical data.
---
3. Common Dataset Formats
• CSV (Comma-Separated Values)
• Excel (.xls, .xlsx)
• JSON (JavaScript Object Notation)
• XML (eXtensible Markup Language)
• Images (JPEG, PNG, TIFF)
• Audio (WAV, MP3)
---
4. Loading Datasets in Python
• Use libraries like
pandas for structured data:import pandas as pd
df = pd.read_csv('data.csv')
• Use libraries like
json for JSON files:import json
with open('data.json') as f:
data = json.load(f)
---
5. Basic Dataset Exploration
• Check shape and size:
print(df.shape)
• Preview data:
print(df.head())
• Check for missing values:
print(df.isnull().sum())
---
6. Summary
• Understanding dataset types is crucial before processing.
• Loading and exploring datasets helps identify cleaning and preprocessing needs.
---
Exercise
• Load a CSV and JSON dataset in Python, print their shapes, and identify missing values.
---
#DataScience #Datasets #DataLoading #Python #DataExploration
The rest of the parts
https://xn--r1a.website/DataScienceM
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Are you a researcher, student, business owner, or developer looking for professional support? We are here to help you turn your ideas into real results! 💡
🔬 1. Scientific Research & Academic Publishing
Professional review and evaluation of scientific manuscripts before submission.
Guidance on journal selection and publication strategies.
Expert advice to improve research quality and presentation.
Support for researchers throughout the academic publishing process.
💻 2. Website & Software Development
Professional website design and development for businesses and individuals.
Custom electronic systems tailored to your needs.
Technical assistance for students and academic projects.
⚙️ 3. API & User Interface (UI) Services
API development and integration.
Modern, responsive, and user-friendly interface design.
Seamless integration between applications and systems.
📊 4. Real-World & Synthetic Datasets
Providing real-world datasets for research and analysis.
Creating customized synthetic datasets according to your requirements.
Data support for scientific research, machine learning, and AI projects.
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Discuss your research ideas and technical projects with us.
Get initial guidance and recommendations.
Explore the best solutions for your academic or professional needs.
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✅ Tailored solutions based on your needs.
✅ Professional guidance and practical support.
✅ Free initial discussion and consultation.
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