🔥 Trending Repository: likec4
📝 Denoscription: Visualize, collaborate, and evolve the software architecture with always actual and live diagrams from your code
🔗 Repository URL: https://github.com/likec4/likec4
🌐 Website: https://likec4.dev
📖 Readme: https://github.com/likec4/likec4#readme
📊 Statistics:
🌟 Stars: 1.4K stars
👀 Watchers: 17
🍴 Forks: 117 forks
💻 Programming Languages: TypeScript - MDX - Astro - JavaScript - CSS - Langium
🏷️ Related Topics:
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
📝 Denoscription: Visualize, collaborate, and evolve the software architecture with always actual and live diagrams from your code
🔗 Repository URL: https://github.com/likec4/likec4
🌐 Website: https://likec4.dev
📖 Readme: https://github.com/likec4/likec4#readme
📊 Statistics:
🌟 Stars: 1.4K stars
👀 Watchers: 17
🍴 Forks: 117 forks
💻 Programming Languages: TypeScript - MDX - Astro - JavaScript - CSS - Langium
🏷️ Related Topics:
#architecture #diagrams #c4 #architecture_as_code
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
There's an entire agent system inside that automates the entire ML creation cycle - from the idea to the finished solution, without manual fiddling with architecture and pipelines.
How it works:
➖ You formulate the task in ordinary text and provide the data. If necessary, the system extracts the schema itself➖ Under the hood, a group of AI agents work: one designs the model, the second writes the code, the third evaluates the quality and corrects errors➖ If there's a lack of data, the system can generate a synthetic dataset for testing➖ There's support for Ray for parallel model exploration and scaling to cores or clusters➖ It connects to any cloud or local models via LiteLLM
It's ideal for rapid prototyping and experiments, when it's important to quickly get a working result - get it here.
https://github.com/plexe-ai/plexe
tags: #useful
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❤2
✅ Data Science Project Ideas
1️⃣ Beginner Friendly Projects
• Exploratory Data Analysis (EDA) on CSV datasets
• Student Marks Analysis
• COVID / Weather Data Analysis
• Simple Data Visualization Dashboard
• Basic Recommendation System (rule-based)
2️⃣ Python for Data Science
• Sales Data Analysis using Pandas
• Web Scraping + Analysis (BeautifulSoup)
• Data Cleaning Preprocessing Project
• Movie Rating Analysis
• Stock Price Analysis (historical data)
3️⃣ Machine Learning Projects
• House Price Prediction
• Spam Email Classifier
• Loan Approval Prediction
• Customer Churn Prediction
• Iris / Titanic Dataset Classification
4️⃣ Data Visualization Projects
• Interactive Dashboard using Matplotlib/Seaborn
• Sales Performance Dashboard
• Social Media Analytics Dashboard
• COVID Trends Visualization
• Country-wise GDP Analysis
5️⃣ NLP (Text Language) Projects
• Sentiment Analysis on Reviews
• Resume Screening System
• Fake News Detection
• Chatbot (Rule-based → ML-based)
• Topic Modeling on Articles
6️⃣ Advanced ML / AI Projects
• Recommendation System (Collaborative Filtering)
• Credit Card Fraud Detection
• Image Classification (CNN basics)
• Face Mask Detection
• Speech-to-Text Analysis
7️⃣ Data Engineering / Big Data
• ETL Pipeline using Python
• Data Warehouse Design (Star Schema)
• Log File Analysis
• API Data Ingestion Project
• Batch Processing with Large Datasets
8️⃣ Real-World / Portfolio Projects
• End-to-End Data Science Project
• Business Problem → Data → Model → Insights
• Kaggle Competition Project
• Open Dataset Case Study
• Automated Data Reporting Tool
1️⃣ Beginner Friendly Projects
• Exploratory Data Analysis (EDA) on CSV datasets
• Student Marks Analysis
• COVID / Weather Data Analysis
• Simple Data Visualization Dashboard
• Basic Recommendation System (rule-based)
2️⃣ Python for Data Science
• Sales Data Analysis using Pandas
• Web Scraping + Analysis (BeautifulSoup)
• Data Cleaning Preprocessing Project
• Movie Rating Analysis
• Stock Price Analysis (historical data)
3️⃣ Machine Learning Projects
• House Price Prediction
• Spam Email Classifier
• Loan Approval Prediction
• Customer Churn Prediction
• Iris / Titanic Dataset Classification
4️⃣ Data Visualization Projects
• Interactive Dashboard using Matplotlib/Seaborn
• Sales Performance Dashboard
• Social Media Analytics Dashboard
• COVID Trends Visualization
• Country-wise GDP Analysis
5️⃣ NLP (Text Language) Projects
• Sentiment Analysis on Reviews
• Resume Screening System
• Fake News Detection
• Chatbot (Rule-based → ML-based)
• Topic Modeling on Articles
6️⃣ Advanced ML / AI Projects
• Recommendation System (Collaborative Filtering)
• Credit Card Fraud Detection
• Image Classification (CNN basics)
• Face Mask Detection
• Speech-to-Text Analysis
7️⃣ Data Engineering / Big Data
• ETL Pipeline using Python
• Data Warehouse Design (Star Schema)
• Log File Analysis
• API Data Ingestion Project
• Batch Processing with Large Datasets
8️⃣ Real-World / Portfolio Projects
• End-to-End Data Science Project
• Business Problem → Data → Model → Insights
• Kaggle Competition Project
• Open Dataset Case Study
• Automated Data Reporting Tool
❤2🔥1
🔥 Trending Repository: cognee
📝 Denoscription: Memory for AI Agents in 6 lines of code
🔗 Repository URL: https://github.com/topoteretes/cognee
🌐 Website: https://www.cognee.ai
📖 Readme: https://github.com/topoteretes/cognee#readme
📊 Statistics:
🌟 Stars: 11.7K stars
👀 Watchers: 59
🍴 Forks: 1.2K forks
💻 Programming Languages: Python - TypeScript - Shell - Dockerfile - CSS - Mako
🏷️ Related Topics:
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
📝 Denoscription: Memory for AI Agents in 6 lines of code
🔗 Repository URL: https://github.com/topoteretes/cognee
🌐 Website: https://www.cognee.ai
📖 Readme: https://github.com/topoteretes/cognee#readme
📊 Statistics:
🌟 Stars: 11.7K stars
👀 Watchers: 59
🍴 Forks: 1.2K forks
💻 Programming Languages: Python - TypeScript - Shell - Dockerfile - CSS - Mako
🏷️ Related Topics:
#open_source #ai #knowledge #neo4j #knowledge_graph #openai #help_wanted #graph_database #ai_agents #contributions_welcome #cognitive_architecture #good_first_issue #rag #good_first_pr #vector_database #graph_rag #ai_memory #cognitive_memory #graphrag #context_engineering
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
❤1
🔥 Trending Repository: fish-shell
📝 Denoscription: The user-friendly command line shell.
🔗 Repository URL: https://github.com/fish-shell/fish-shell
🌐 Website: https://fishshell.com
📖 Readme: https://github.com/fish-shell/fish-shell#readme
📊 Statistics:
🌟 Stars: 32.3K stars
👀 Watchers: 279
🍴 Forks: 2.2K forks
💻 Programming Languages: Rust - Shell - Python - HTML - JavaScript - CMake
🏷️ Related Topics:
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
📝 Denoscription: The user-friendly command line shell.
🔗 Repository URL: https://github.com/fish-shell/fish-shell
🌐 Website: https://fishshell.com
📖 Readme: https://github.com/fish-shell/fish-shell#readme
📊 Statistics:
🌟 Stars: 32.3K stars
👀 Watchers: 279
🍴 Forks: 2.2K forks
💻 Programming Languages: Rust - Shell - Python - HTML - JavaScript - CMake
🏷️ Related Topics:
#shell #rust #fish #terminal
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
❤1
🔥 Trending Repository: prompt-optimizer
📝 Denoscription: 一款提示词优化器，助力于编写高质量的提示词
🔗 Repository URL: https://github.com/linshenkx/prompt-optimizer
🌐 Website: https://prompt.always200.com
📖 Readme: https://github.com/linshenkx/prompt-optimizer#readme
📊 Statistics:
🌟 Stars: 19.2K stars
👀 Watchers: 77
🍴 Forks: 2.4K forks
💻 Programming Languages: TypeScript - Vue - JavaScript - Shell - CSS - Dockerfile
🏷️ Related Topics:
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
📝 Denoscription: 一款提示词优化器，助力于编写高质量的提示词
🔗 Repository URL: https://github.com/linshenkx/prompt-optimizer
🌐 Website: https://prompt.always200.com
📖 Readme: https://github.com/linshenkx/prompt-optimizer#readme
📊 Statistics:
🌟 Stars: 19.2K stars
👀 Watchers: 77
🍴 Forks: 2.4K forks
💻 Programming Languages: TypeScript - Vue - JavaScript - Shell - CSS - Dockerfile
🏷️ Related Topics:
#prompt #prompt_toolkit #prompt_tuning #llm #prompt_engineering #prompt_optimization
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
❤2
🔥 Trending Repository: anet
📝 Denoscription: Simple Rust VPN Client / Server
🔗 Repository URL: https://github.com/ZeroTworu/anet
📖 Readme: https://github.com/ZeroTworu/anet#readme
📊 Statistics:
🌟 Stars: 268 stars
👀 Watchers: 15
🍴 Forks: 20 forks
💻 Programming Languages: Rust - Inno Setup - Shell - Makefile
🏷️ Related Topics:
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
📝 Denoscription: Simple Rust VPN Client / Server
🔗 Repository URL: https://github.com/ZeroTworu/anet
📖 Readme: https://github.com/ZeroTworu/anet#readme
📊 Statistics:
🌟 Stars: 268 stars
👀 Watchers: 15
🍴 Forks: 20 forks
💻 Programming Languages: Rust - Inno Setup - Shell - Makefile
🏷️ Related Topics:
#rust #vpn
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
❤2
🔥 Trending Repository: data-engineer-handbook
📝 Denoscription: This is a repo with links to everything you'd ever want to learn about data engineering
🔗 Repository URL: https://github.com/DataExpert-io/data-engineer-handbook
📖 Readme: https://github.com/DataExpert-io/data-engineer-handbook#readme
📊 Statistics:
🌟 Stars: 39.7K stars
👀 Watchers: 466
🍴 Forks: 7.6K forks
💻 Programming Languages: Jupyter Notebook - Python - Makefile - Dockerfile - Shell
🏷️ Related Topics:
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
📝 Denoscription: This is a repo with links to everything you'd ever want to learn about data engineering
🔗 Repository URL: https://github.com/DataExpert-io/data-engineer-handbook
📖 Readme: https://github.com/DataExpert-io/data-engineer-handbook#readme
📊 Statistics:
🌟 Stars: 39.7K stars
👀 Watchers: 466
🍴 Forks: 7.6K forks
💻 Programming Languages: Jupyter Notebook - Python - Makefile - Dockerfile - Shell
🏷️ Related Topics:
#data #awesome #sql #bigdata #dataengineering #apachespark
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
❤1
Data Science Interview Prep Guide
1️⃣ Core Data Science Concepts
• What is Data Science vs Data Analytics vs ML
• Denoscriptive, diagnostic, predictive, prenoscriptive analytics
• Structured vs unstructured data
• Data-driven decision making
• Business problem framing
2️⃣ Statistics Probability (Non-Negotiable)
• Mean, median, variance, standard deviation
• Probability distributions (normal, binomial, Poisson)
• Hypothesis testing p-values
• Confidence intervals
• Correlation vs causation
• Sampling bias
3️⃣ Data Cleaning EDA
• Handling missing values outliers
• Data normalization scaling
• Feature engineering
• Exploratory data analysis (EDA)
• Data leakage detection
• Data quality validation
4️⃣ Python SQL for Data Science
• Python (NumPy, Pandas)
• Data manipulation transformations
• Vectorization performance optimization
• SQL joins, CTEs, window functions
• Writing business-ready queries
5️⃣ Machine Learning Essentials
• Supervised vs unsupervised learning
• Regression vs classification
• Model selection baseline models
• Overfitting, underfitting
• Bias–variance tradeoff
• Hyperparameter tuning
6️⃣ Model Evaluation Metrics
• Accuracy, precision, recall, F1
• ROC AUC
• Confusion matrix
• RMSE, MAE, log loss
• Metrics for imbalanced data
• Linking ML metrics to business KPIs
7️⃣ Real-World Deployment Knowledge
• Feature stores
• Model deployment (batch vs real-time)
• Model monitoring drift
• Experiment tracking
• Data model versioning
• Model explainability (business-friendly)
8️⃣ Must-Have Projects
• Customer churn prediction
• Fraud detection
• Sales or demand forecasting
• Recommendation system
• End-to-end ML pipeline
• Business-focused case study
9️⃣ Common Interview Questions
• Walk me through an end-to-end DS project
• How do you choose evaluation metrics?
• How do you handle imbalanced data?
• How do you explain a model to leadership?
• How do you improve a failing model?
🔟 Pro Tips
✔️ Always connect answers to business impact
✔️ Explain why, not just how
✔️ Be clear about trade-offs
✔️ Discuss failures learnings
✔️ Show structured thinking
https://news.1rj.ru/str/DataScienceN
1️⃣ Core Data Science Concepts
• What is Data Science vs Data Analytics vs ML
• Denoscriptive, diagnostic, predictive, prenoscriptive analytics
• Structured vs unstructured data
• Data-driven decision making
• Business problem framing
2️⃣ Statistics Probability (Non-Negotiable)
• Mean, median, variance, standard deviation
• Probability distributions (normal, binomial, Poisson)
• Hypothesis testing p-values
• Confidence intervals
• Correlation vs causation
• Sampling bias
3️⃣ Data Cleaning EDA
• Handling missing values outliers
• Data normalization scaling
• Feature engineering
• Exploratory data analysis (EDA)
• Data leakage detection
• Data quality validation
4️⃣ Python SQL for Data Science
• Python (NumPy, Pandas)
• Data manipulation transformations
• Vectorization performance optimization
• SQL joins, CTEs, window functions
• Writing business-ready queries
5️⃣ Machine Learning Essentials
• Supervised vs unsupervised learning
• Regression vs classification
• Model selection baseline models
• Overfitting, underfitting
• Bias–variance tradeoff
• Hyperparameter tuning
6️⃣ Model Evaluation Metrics
• Accuracy, precision, recall, F1
• ROC AUC
• Confusion matrix
• RMSE, MAE, log loss
• Metrics for imbalanced data
• Linking ML metrics to business KPIs
7️⃣ Real-World Deployment Knowledge
• Feature stores
• Model deployment (batch vs real-time)
• Model monitoring drift
• Experiment tracking
• Data model versioning
• Model explainability (business-friendly)
8️⃣ Must-Have Projects
• Customer churn prediction
• Fraud detection
• Sales or demand forecasting
• Recommendation system
• End-to-end ML pipeline
• Business-focused case study
9️⃣ Common Interview Questions
• Walk me through an end-to-end DS project
• How do you choose evaluation metrics?
• How do you handle imbalanced data?
• How do you explain a model to leadership?
• How do you improve a failing model?
🔟 Pro Tips
✔️ Always connect answers to business impact
✔️ Explain why, not just how
✔️ Be clear about trade-offs
✔️ Discuss failures learnings
✔️ Show structured thinking
https://news.1rj.ru/str/DataScienceN
❤5
Data Science Jupyter Notebooks
Data Science Interview Prep Guide 1️⃣ Core Data Science Concepts • What is Data Science vs Data Analytics vs ML • Denoscriptive, diagnostic, predictive, prenoscriptive analytics • Structured vs unstructured data • Data-driven decision making • Business problem…
If you’re prepping for a data science role, this guide has EVERYTHING you need. Check it out! 💡
❤3
🔥 Trending Repository: shannon
📝 Denoscription: Fully autonomous AI hacker to find actual exploits in your web apps. Shannon has achieved a 96.15% success rate on the hint-free, source-aware XBOW Benchmark.
🔗 Repository URL: https://github.com/KeygraphHQ/shannon
🌐 Website: https://keygraph.io/
📖 Readme: https://github.com/KeygraphHQ/shannon#readme
📊 Statistics:
🌟 Stars: 7.9K stars
👀 Watchers: 63
🍴 Forks: 1.1K forks
💻 Programming Languages: TypeScript - JavaScript - Shell - Dockerfile
🏷️ Related Topics:
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
📝 Denoscription: Fully autonomous AI hacker to find actual exploits in your web apps. Shannon has achieved a 96.15% success rate on the hint-free, source-aware XBOW Benchmark.
🔗 Repository URL: https://github.com/KeygraphHQ/shannon
🌐 Website: https://keygraph.io/
📖 Readme: https://github.com/KeygraphHQ/shannon#readme
📊 Statistics:
🌟 Stars: 7.9K stars
👀 Watchers: 63
🍴 Forks: 1.1K forks
💻 Programming Languages: TypeScript - JavaScript - Shell - Dockerfile
🏷️ Related Topics:
#security_audit #penetration_testing #pentesting #security_automation #security_tools
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
🔥 Trending Repository: litebox
📝 Denoscription: A security-focused library OS supporting kernel- and user-mode execution
🔗 Repository URL: https://github.com/microsoft/litebox
📖 Readme: https://github.com/microsoft/litebox#readme
📊 Statistics:
🌟 Stars: 914 stars
👀 Watchers: 11
🍴 Forks: 40 forks
💻 Programming Languages: Rust - C - JavaScript - CSS - Assembly - Python
🏷️ Related Topics: Not available
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
📝 Denoscription: A security-focused library OS supporting kernel- and user-mode execution
🔗 Repository URL: https://github.com/microsoft/litebox
📖 Readme: https://github.com/microsoft/litebox#readme
📊 Statistics:
🌟 Stars: 914 stars
👀 Watchers: 11
🍴 Forks: 40 forks
💻 Programming Languages: Rust - C - JavaScript - CSS - Assembly - Python
🏷️ Related Topics: Not available
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
🔥 Trending Repository: heretic
📝 Denoscription: Fully automatic censorship removal for language models
🔗 Repository URL: https://github.com/p-e-w/heretic
📖 Readme: https://github.com/p-e-w/heretic#readme
📊 Statistics:
🌟 Stars: 4.5K stars
👀 Watchers: 27
🍴 Forks: 441 forks
💻 Programming Languages: Python
🏷️ Related Topics:
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
📝 Denoscription: Fully automatic censorship removal for language models
🔗 Repository URL: https://github.com/p-e-w/heretic
📖 Readme: https://github.com/p-e-w/heretic#readme
📊 Statistics:
🌟 Stars: 4.5K stars
👀 Watchers: 27
🍴 Forks: 441 forks
💻 Programming Languages: Python
🏷️ Related Topics:
#transformer #llm #abliteration
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
🔥 Trending Repository: MiniCPM-o
📝 Denoscription: A Gemini 2.5 Flash Level MLLM for Vision, Speech, and Full-Duplex Multimodal Live Streaming on Your Phone
🔗 Repository URL: https://github.com/OpenBMB/MiniCPM-o
📖 Readme: https://github.com/OpenBMB/MiniCPM-o#readme
📊 Statistics:
🌟 Stars: 23.1K stars
👀 Watchers: 156
🍴 Forks: 1.8K forks
💻 Programming Languages: Python - Vue - JavaScript - Shell - Less - CSS
🏷️ Related Topics:
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
📝 Denoscription: A Gemini 2.5 Flash Level MLLM for Vision, Speech, and Full-Duplex Multimodal Live Streaming on Your Phone
🔗 Repository URL: https://github.com/OpenBMB/MiniCPM-o
📖 Readme: https://github.com/OpenBMB/MiniCPM-o#readme
📊 Statistics:
🌟 Stars: 23.1K stars
👀 Watchers: 156
🍴 Forks: 1.8K forks
💻 Programming Languages: Python - Vue - JavaScript - Shell - Less - CSS
🏷️ Related Topics:
#multi_modal #minicpm #minicpm_v
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
🔥 Trending Repository: escrcpy
📝 Denoscription: 📱 Display and control your Android device graphically with scrcpy.
🔗 Repository URL: https://github.com/viarotel-org/escrcpy
🌐 Website: https://viarotel.eu.org/
📖 Readme: https://github.com/viarotel-org/escrcpy#readme
📊 Statistics:
🌟 Stars: 7.7K stars
👀 Watchers: 48
🍴 Forks: 563 forks
💻 Programming Languages: JavaScript - Vue - TypeScript - Roff - CSS - VBScript
🏷️ Related Topics:
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
📝 Denoscription: 📱 Display and control your Android device graphically with scrcpy.
🔗 Repository URL: https://github.com/viarotel-org/escrcpy
🌐 Website: https://viarotel.eu.org/
📖 Readme: https://github.com/viarotel-org/escrcpy#readme
📊 Statistics:
🌟 Stars: 7.7K stars
👀 Watchers: 48
🍴 Forks: 563 forks
💻 Programming Languages: JavaScript - Vue - TypeScript - Roff - CSS - VBScript
🏷️ Related Topics:
#android #windows #macos #linux #screenshots #gui #recording #screensharing #mirroring #hacktoberfest #scrcpy #scrcpy_engine #gnirehtet #genymobile #scrcpy_gui #hacktoberfest2025 #hacktoberfest2026
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
🔥 Trending Repository: awesome-claude-skills
📝 Denoscription: A curated list of awesome Claude Skills, resources, and tools for customizing Claude AI workflows
🔗 Repository URL: https://github.com/ComposioHQ/awesome-claude-skills
📖 Readme: https://github.com/ComposioHQ/awesome-claude-skills#readme
📊 Statistics:
🌟 Stars: 31.5K stars
👀 Watchers: 244
🍴 Forks: 3K forks
💻 Programming Languages: Python - JavaScript - Shell
🏷️ Related Topics:
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
📝 Denoscription: A curated list of awesome Claude Skills, resources, and tools for customizing Claude AI workflows
🔗 Repository URL: https://github.com/ComposioHQ/awesome-claude-skills
📖 Readme: https://github.com/ComposioHQ/awesome-claude-skills#readme
📊 Statistics:
🌟 Stars: 31.5K stars
👀 Watchers: 244
🍴 Forks: 3K forks
💻 Programming Languages: Python - JavaScript - Shell
🏷️ Related Topics:
#automation #skill #mcp #saas #cursor #codex #workflow_automation #ai_agents #claude #rube #gemini_cli #composio #antigravity #agent_skills #claude_code
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
🔥 Trending Repository: gitbutler
📝 Denoscription: The GitButler version control client, backed by Git, powered by Tauri/Rust/Svelte
🔗 Repository URL: https://github.com/gitbutlerapp/gitbutler
🌐 Website: https://gitbutler.com
📖 Readme: https://github.com/gitbutlerapp/gitbutler#readme
📊 Statistics:
🌟 Stars: 17.7K stars
👀 Watchers: 47
🍴 Forks: 768 forks
💻 Programming Languages: Rust - Svelte - TypeScript - Shell - CSS - JavaScript
🏷️ Related Topics:
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
📝 Denoscription: The GitButler version control client, backed by Git, powered by Tauri/Rust/Svelte
🔗 Repository URL: https://github.com/gitbutlerapp/gitbutler
🌐 Website: https://gitbutler.com
📖 Readme: https://github.com/gitbutlerapp/gitbutler#readme
📊 Statistics:
🌟 Stars: 17.7K stars
👀 Watchers: 47
🍴 Forks: 768 forks
💻 Programming Languages: Rust - Svelte - TypeScript - Shell - CSS - JavaScript
🏷️ Related Topics:
#github #git #tauri
==================================
🧠 By: https://news.1rj.ru/str/DataScienceM
One day or Day one. You decide.
Data Science edition.
𝗢𝗻𝗲 𝗗𝗮𝘆 : I will learn SQL.
𝗗𝗮𝘆 𝗢𝗻𝗲: Download mySQL Workbench.
𝗢𝗻𝗲 𝗗𝗮𝘆: I will build my projects for my portfolio.
𝗗𝗮𝘆 𝗢𝗻𝗲: Look on Kaggle for a dataset to work on.
𝗢𝗻𝗲 𝗗𝗮𝘆: I will master statistics.
𝗗𝗮𝘆 𝗢𝗻𝗲: Start the free Khan Academy Statistics and Probability course.
𝗢𝗻𝗲 𝗗𝗮𝘆: I will learn to tell stories with data.
𝗗𝗮𝘆 𝗢𝗻𝗲: Install Tableau Public and create my first chart.
𝗢𝗻𝗲 𝗗𝗮𝘆: I will become a Data Scientist.
𝗗𝗮𝘆 𝗢𝗻𝗲: Update my resume and apply to some Data Science job postings.
https://news.1rj.ru/str/DataScienceN
Data Science edition.
𝗢𝗻𝗲 𝗗𝗮𝘆 : I will learn SQL.
𝗗𝗮𝘆 𝗢𝗻𝗲: Download mySQL Workbench.
𝗢𝗻𝗲 𝗗𝗮𝘆: I will build my projects for my portfolio.
𝗗𝗮𝘆 𝗢𝗻𝗲: Look on Kaggle for a dataset to work on.
𝗢𝗻𝗲 𝗗𝗮𝘆: I will master statistics.
𝗗𝗮𝘆 𝗢𝗻𝗲: Start the free Khan Academy Statistics and Probability course.
𝗢𝗻𝗲 𝗗𝗮𝘆: I will learn to tell stories with data.
𝗗𝗮𝘆 𝗢𝗻𝗲: Install Tableau Public and create my first chart.
𝗢𝗻𝗲 𝗗𝗮𝘆: I will become a Data Scientist.
𝗗𝗮𝘆 𝗢𝗻𝗲: Update my resume and apply to some Data Science job postings.
https://news.1rj.ru/str/DataScienceN
❤6
Data Science Jupyter Notebooks
One day or Day one. You decide. Data Science edition. 𝗢𝗻𝗲 𝗗𝗮𝘆 : I will learn SQL. 𝗗𝗮𝘆 𝗢𝗻𝗲: Download mySQL Workbench. 𝗢𝗻𝗲 𝗗𝗮𝘆: I will build my projects for my portfolio. 𝗗𝗮𝘆 𝗢𝗻𝗲: Look on Kaggle for a dataset to work on. 𝗢𝗻𝗲 𝗗𝗮𝘆: I will master statistics.…
Don’t wait for the perfect moment. Start today
Install that tool, pick that dataset, take that course. Every big goal begins with Day One 💪
Install that tool, pick that dataset, take that course. Every big goal begins with Day One 💪
❤4
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