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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-projects-for-healthcare/
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课程名称：医疗保健的机器学习项目 课程概述：医疗保健领域的机器学习项目正日益普及，数据科学的应用遍及我们的日常生活。各个领域都在变革中使用数据科学技术，包括医疗、信息技术、媒体、娱乐等。如今，医疗行业正成功利用数据科学的力量，课程将探讨数据科学在医疗保健中的应用。为提升未来的护理效果，医生所接收到的电子信息亟需通过分析和机器学习的能力进行增强。本课程适合初学者和具备一定Python及机器学习技能的学习者，专注于医疗保健项目，因为医疗领域在人工智能和机器学习方面有着巨大的发展潜力，许多创新有待被揭示。我们致力于参与这些动态项目，帮助学员深入理解行业的广阔视角，从而促进职业发展。 课程详尽涵盖了多种算法，确保学习者对概念有透彻的理解。虽然机器学习使用预先开发的算法，但要真正将优秀模型转化为卓越模型，还需对背后的运行机制有清晰的认识。此外，我们重点探索市场需求的行业级项目，以提供解决问题的实时体验。本课程旨在以实用易懂的方式向学生讲授神经网络和机器学习技术的关键方面。 课程项目包括： - 帕金森病检测 - 慢性肾病预测 - 利用PyCaret进行肝脏疾病预测 课程内容还涵盖人工智能的类型及其差异、机器学习的基本原则、神经网络的概念、深度学习与预测分析的应用等。这些技术在提高患者护理和慢性疾病管理方面扮演重要角色，数据驱动的方法聚焦于预防社会普遍疾病。 在医疗保健领域，尽管已取得多项进展，未来仍需更多应用和改善，如数字化、技术整合、降低治疗成本，以及处理大量患者信息的能力。数据科学工具和技术正在为这些需求提供支持，并取得显著进展，未来将为医生和患者的护理提供更多帮助。 适合对象：所有级别的学习者，包括初学者、中级和高级用户。
Machine Learning projects for HealthcareData Science applications are everywhere in our regular life.Every sector is revolutionizing Data Science applications, including Healthcare, IT, Media, Entertainment, and many others.Today, healthcare industries are utilizing the power of Data Science successfully, and today we are going to disclose the use of Data Science in Healthcare.If technology is to improve care in the future, then the electronic information provided to doctors needs to be enhanced by the power of analytics and machine learning.This course is designed for both beginners & experienced with some python & machine learning skills.As we are more focusing on healthcare project since Healthcare has lot of scope to develop into Artificial Intelligence and machine learning sector. Many innovations are yet to revealed. We as a pioneer trying to indulge into such dynamics projects which will not only give you broader perspective of this industry but will help you to get a career growth.Many algorithms are covered in detail so that the learner gains good understanding of the concepts. Although Machine Learning involves use of pre-developed algorithms one needs to have a clear understanding of what goes behind the scene to actually convert a good model to a great model.Moreover, our focus is to explore industry grade projects which are demanded in the market will give real time experience while solving it.The purpose of this course is to provide students with knowledge of key aspects of neural networks and machine learning techniques in a practical, easy way. Th projects included are:Detecting Parkinson's DiseasePrediction of Chronic Kidney DiseasePrediction of Liver Disease using PyCaretTypes of AI and how do they differ?Artificial IntelligenceA feature where machines learn to perform tasks, rather than simply carrying out computations that are input by human users.Machine LearningAn approach to AI in which a computer algorithm (a set of rules and procedures) is developed to analyze and make predictions from data that is fed into the system.Neural NetworksA machine learning approach modeled after the brain in which algorithms process signals via interconnected nodes called artificial neurons.Mimicking biological nervous systems, artificial neural networks have been used successfully to recognize and predict patterns of neural signals involved in brain function.Deep LearningA form of machine learning that uses many layers of computation to form what is described as a deep neural network, capable of learning from large amounts of complex, unstructured data.Predictive AnalyticsPredictive Analytics is playing an important role in improving patient care, chronic disease management.Population health management is becoming an increasingly popular topic in predictive analytics. It is a data-driven approach focusing on prevention of diseases that are commonly prevalent in society.With data science, hospitals can predict the deterioration in patient's health and provide preventive measures and start an early treatment that will assist in reducing the risk of the further aggravation of patient health.Future of Data Science in HealthcareThere have been many improvements done in the healthcare sector, but still, some more applications and improvements are required in the future like: digitization, technological inclusion, reduced cost of treatment, need to be able to handle huge amount of patient's information.Data science tools and technologies are working for these requirements and have made many improvements as well. Data science is doing wonders in many real-life areas and contributing a lot. There will be much assistance available for doctors and patients through this revolution of data science in the future.Who this course is for:Beginner LevelIntermediate LevelAdvanced LevelAll Levels
