In this course, we’ll learn about more advanced machine learning methods that are used to tackle problems in the supply chain. We’ll start with an overview of the different ML paradigms (regression/classification) and where the latest models fit into these breakdowns. Then, we’ll dive deeper into some of the specific techniques and use cases such as using neural networks to predict product demand and random forests to classify products. An important part to using these models is understanding their assumptions and required preprocessing steps. We’ll end with a project incorporating advanced techniques with an image classification problem to find faulty products coming out of a machine.
Este curso forma parte de Programa especializado: Machine Learning for Supply Chains
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Acerca de este Curso
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Fechas límite flexibles
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100 % en línea
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Curso 3 de 4 en
Nivel intermedio
It is reccomended that you finish the first two courses in the speciliation before trying this one.
Aprox. 22 horas para completar
Inglés (English)
Subtítulos: Inglés (English)
Habilidades que obtendrás
- Natural Language Processing
- Machine Learning
- Bias–Variance Tradeoff
- Supply Chain
- Image Analysis
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Curso 3 de 4 en
Nivel intermedio
It is reccomended that you finish the first two courses in the speciliation before trying this one.
Aprox. 22 horas para completar
Inglés (English)
Subtítulos: Inglés (English)
ofrecido por
LearnQuest
LearnQuest is the preferred training partner to the world’s leading companies, organizations, and government agencies. Our team boasts 20+ years of experience designing, developing and delivering a full suite industry-leading technology education classes and training solutions across the globe. Our trainers, equipped with expert industry experience and an unparalleled commitment to quality, facilitate classes that are offered in various delivery formats so our clients can obtain the training they need when and where they need it.
Programa - Qué aprenderás en este curso
2 horas para completar
Machine Learning in the Supply Chain
In this module, we'll learn about the use cases of machine learning in the supply chain. We'll start with the big picture applications before diving deeper into specific algorithms, including neural networks. Throughout the module, we'll explain not only the general artificial intelligence concepts and mathematics, but also how these algorithms can specifically be used for the supply chain.
2 horas para completar
4 videos (Total 11 minutos), 4 lecturas, 2 cuestionarios
14 horas para completar
A Classical AI Approach
In this module, we'll cover the concepts relating to the ML paradigm. We'll start by learning how to pick a model, relying on considerations such as managing the bias-variance tradeoff. Next, we'll explore how machine learning models converge, including the use of stochastic gradient descent to minimize loss functions. Finally, we'll end with some practical considerations on coding advanced AI models with libraries for hyperparamter tuning.
14 horas para completar
3 videos (Total 9 minutos), 4 lecturas, 2 cuestionarios
3 horas para completar
Images and Text
In this module, we'll expand beyond numbers and learn how to use machine learning on images and text. We'll start by talking about how to analyze text data and cover the primary methods behind natural language processing. Then, we'll learn how to analyze images by constructing convolutional neural networks complete with convolutions and pooling layers.
3 horas para completar
5 videos (Total 19 minutos), 5 lecturas, 1 cuestionario
4 horas para completar
Final Project: Detecting Anomalies with Image Classification
In this final project, we’ll apply what we learned in the last module to classify images of products based on whether there is a defect or not.
4 horas para completar
Acerca de Programa especializado: Machine Learning for Supply Chains
This specialization is intended for students who wish to use machine language to analyze and predict product usage and other similar tasks. There is no specific prerequisite but some general knowledge of supply chain will be helpful, as well as general statistics and calculus.
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