With the development of the society, people's material needs are increasing rapidly. Based on this background, intelligent household furniture products with high-tech content are integrated into the eld of interior design, and then gradually in ltrated into people's production and life. And from a smart technology perspective, we analyze the art design of smart home products based on machine learning algorithm. This algorithm can make the actual classi cation results of the test samples consistent with the network output values, and the error values can also meet the accuracy requirements, so as to effectively determine the defect types of the parameter samples. Among them, the art design of smart home products includes home equipment network group, embedded gateway implementation, cloud server construction and interaction design, independent product auxiliary control system and other parts. Finally, through the simulation test results of the intelligent positioning function of the product, we can know that the communication e ciency of the product basically meets the requirements. Interior design products are indispensable in people's home life, and play an important role in the whole indoor environment, such as art paintings, bonsai, woven art, etc. In addition, household appliances and lamps will also affect the aesthetic feeling of the whole interior design. This study tries to introduce machine learning technology in the eld of interior art design to make it more intelligent, and a kind of effective algorithm design is completed.
With the development of the society, people's material needs are increasing rapidly. Based on this background, intelligent household furniture products with high-tech content are integrated into the field of interior design, and then gradually infiltrated into people's production and life. And from a smart technology perspective, we analyze the art design of smart home products based on machine learning algorithm. This algorithm can make the actual classification results of the test samples consistent with the network output values, and the error values can also meet the accuracy requirements, so as to effectively determine the defect types of the parameter samples. Among them, the art design of smart home products includes home equipment network group, embedded gateway implementation, cloud server construction and interaction design, independent product auxiliary control system and other parts. Finally, through the simulation test results of the intelligent positioning function of the product, we can know that the communication efficiency of the product basically meets the requirements. Interior design products are indispensable in people's home life, and play an important role in the whole indoor environment, such as art paintings, bonsai, woven art, etc. In addition, household appliances and lamps will also affect the aesthetic feeling of the whole interior design. This study tries to introduce machine learning technology in the field of interior art design to make it more intelligent, and a kind of effective algorithm design is completed.
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