Scikit-learn, PyTorch, and TensorFlow remain core tools for structured data and deep learning tasks.New libraries like JAX, Polars, and LangChain ...

Since the consuming behavior of customers is hard to predict and most data is diversified and unclassified in the real world, it is of great importance to collect those data and analyze them so as to ...

This study presents a comprehensive survey on Quantum Machine Learning (QML) along with its current status, challenges, and perspectives. QML combines quantum computing and machine learning to solve ...

Key Takeaways The transition requires upskilling in Python, statistics, and machine learning.Practical experience with ...

Isolation Forest detects anomalies by isolating observations. It builds binary trees (called iTrees) by recursively ...

We speak to Cern principal scientist Archana Sharma about pattern recognition, machine learning and quantum technology.