In 2025, data science will continue to evolve rapidly. Here are 10 key trends to watch:
AI-Powered Automation – End-to-end machine learning pipelines with minimal human input.
TinyML – Running ML on edge devices with low power and memory.
Synthetic Data – Using AI to generate training data when real data is scarce.
Explainable AI (XAI) – Transparent, interpretable models for ethical AI use.
Data-Centric AI – Prioritizing high-quality, well-labeled data over complex models.
Privacy-Preserving ML – Techniques like federated learning to secure user data.
Multimodal Learning – Combining text, audio, video, and images for deeper insights.
AutoML 2.0 – Smarter, faster tools for non-experts to build models.
AI Governance – Stronger regulation and monitoring of AI systems.
Industry-Specific AI – Tailored solutions for healthcare, finance, retail, and more.
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