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Understand the field, strengthen statistical knowledge, learn Python and libraries, build projects, network, and prepare for interviews. Consider projects like predictive modeling, NLP, image classification, recommendation systems, and time series analysis. Persistence and continuous learning are key. And all the Best.
AI Deep Explorer | f... • 10m
AI Resources for Beginners Books: 1. Deep Learning. Illustrated Edition. Ian Goodfellow, Yoshua Bengio, and Aaron Courville. 2. Mathematics for Machine Learning. Deisenroth, A. Aldo Faisal, and Cheng Soon Ong. 3. Reinforcement learning, An Introd
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Digital twins are live virtual replicas of physical systems that combine IoT sensor data, physics- and data-driven modeling, and analytics/ML to mirror real-time conditions. Their core components are continuous data input, dynamic modeling, and predi
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StockWise: Unlocking Seasonal Stock Trends with Data Science StockWise is a data-driven stock market research startup focused on identifying seasonal stocks—stocks that consistently exhibit 20-30% price movements in specific months over a decade or
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