Memory Optimization Techniques
Memory optimization techniques refer to the methods and strategies used to reduce the amount of memory required to store and process data in computer systems. These techniques are particularly important in the field of data science and artificial intelligence, where large datasets and complex algorithms can quickly consume vast amounts of memory. Some common memory optimization techniques include data compression, caching, and lazy evaluation. Data compression involves reducing the size of data by removing redundant or unnecessary information, while caching involves storing frequently accessed data in a faster, more accessible location. Lazy evaluation involves delaying the evaluation of an expression until it is actually needed, which can help to conserve memory by avoiding the creation of unnecessary data structures.
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