Machine Learning Engineering

AI has become an incredibly hot topic in recent years, and it continues to garner significant attention and interest from people all around the world. The development and release of models like ChatGPT, as well as advancements in generative AI, have opened up new possibilities and sparked curiosity among individuals wanting to learn more about AI. Nevertheless, effectively deploying a model can be a challenging endeavor. According to Deeplearning.ai, a mere 22% of companies utilizing machine learning have achieved successful model deployment. This difficulty arises from the utilization of real-world data in machine learning, which constantly undergoes changes and disorder, thereby elongating and complicating the deployment process.