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Lists, dictionaries, tuples, and sets. (Dictionaries are especially critical for handling JSON data from AI APIs).
To understand and implement classical machine learning algorithms. The community provided Rohan with motivation, support, and
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Use alongside PyTorch to build systems that see. Key projects include building real-time face detection systems, automated object tracking, and optical character recognition (OCR) tools. Natural Language Processing (NLP) Lists, dictionaries, tuples, and sets
You must learn the "Big Three" libraries for data manipulation:
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An Image Classifier that distinguishes between different types of plants or animals using a CNN in PyTorch. Artificial Intelligence (AI) is no longer a futuristic
Ordered, mutable sequences used to store collections of data features.
Data scientists rarely work with single variables. You must master Python's built-in collections:
Before any AI model can be built, data must be loaded, cleaned, and transformed. provides the foundation for numerical computing with its powerful N-dimensional array objects. Pandas builds on this, offering high-level data structures like DataFrames, making it easy to manipulate and analyze tabular data. Almost every line of data science code you write will involve these two libraries.
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