Data Scientist’s Toolkit- A Mind map
Comprehensive set of skills and tools crucial for any data scientist
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In this mind map, I’ve organized a comprehensive set of skills and tools crucial for any data scientist. The programming languages section covers the fundamentals, including Python with powerful libraries such as NumPy, Pandas, Scikit-learn, and R and SQL. Moving to data manipulation and analysis, Pandas, NumPy, and Dplyr for R are highlighted, forming the backbone of efficient data handling. The data visualization category introduces tools like Matplotlib, Seaborn, Plotly, and Tableau, ensuring effective communication of insights. For machine learning enthusiasts, the mind map outlines key libraries such as Scikit-learn, TensorFlow, PyTorch, and advanced techniques like XGBoost and LightGBM. Statistical analysis incorporates essential concepts such as neural networks, Keras, convolutional neural networks (CNN), and recurrent neural networks (RNN). Lastly, the mind map includes natural language processing (NLP) tools like NLTK, and SpaCy, and advanced models like Transformers (e.g., BERT and GPT), facilitating the exploration of text data. This mind map serves as a valuable reference for both beginners and experienced data scientists, offering a structured overview of the diverse…
