The artificial intelligence (AI) market is growing fast. One powerful subset of AI is machine learning (ML), which involves not predefined instructions and fixed algorithms but learned patterns over artificial neural networks. Developers have used ML to solve mission-critical problems with high speed and accuracy in a wide range of domains, including agriculture, e-commerce, education, finance, manufacturing, medicine, networking, transportation and more.
For many IT practitioners and consultants, ML is a matter of not if but when and how. They are asking themselves questions such as, « What’s my use case, design and scale? Which ML techniques will I deploy (language processing, classification, anomaly detection, etc.)? How will I deploy—DIY or with external help—and train the model? »
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