Complete A. I. & Machine Learning, Data Science Bootcamp

所在平台: Udemy

课程主页: https://www.udemy.com/course/complete-machine-learning-and-data-science-zero-to-mastery/

课程评论:没有评论

第一个写评论        关注课程

课程简介

课程名称:完全的人工智能与机器学习、数据科学训练营 课程概述: 本课程旨在帮助学员全面掌握人工智能、数据科学及机器学习的技能。课程由来自硅谷和多伦多的大型公司工作的行业专家授课,现已吸引超过900,000名工程师加入。通过参与该课程,学员将从零开始学习数据科学与机器学习,最终能够在Google、Tesla、Amazon等顶尖科技公司获得工作。 课程内容采用现代化、项目驱动的方式,围绕实际项目进行教学,确保学员能够在学习过程中积累实战经验并建立自己的作品集。学员将获得所有代码、工作簿和模板的访问权限,以便于快速将其纳入自己的作品集中。课程强调效率,避免使用复杂、过时或不完整的机器学习教程。 课程设置分为两个学习路径:如果学员已有编程基础,可以直接进入更高级的内容;否则,将从Python基础开始逐步深入。目前课程使用最新版本的Python和TensorFlow 2.0等库,涵盖以下主题: - 数据探索与可视化 - 神经网络与深度学习 - 模型评估与分析 - Python 3编程 - TensorFlow 2.0、Numpy、Scikit-Learn - 数据科学与机器学习项目和工作流 - Python中的数据可视化(Matplotlib和Seaborn) - 迁移学习、图像识别与分类 - 监督学习(分类、回归和时间序列) - 决策树与随机森林 - 超参数调整与使用Pandas处理数据帧 通过本课程,学员将能够完成一系列实际项目,例如心脏病检测、推土机价格预测、犬种图像分类等,建立起可以向他人展示的项目组合。课程不仅教授知识和技能,还激励学员独立解决实际机器学习问题。 课程适合所有希望提升数据科学技能的人士,无论是编程初学者还是希望在这一领域提升自己的专业人士。其他涉及的内容还有大数据技术(如Hadoop、Apache Spark等)、GPU的使用以及机器学习在各行各业的应用等。 授课老师Daniel Bourke和Andrei Neagoie均为自学成才的行业专家,致力于为学生提供高效的学习体验,并帮助学生掌握现实生活中的技能与知识。 立即报名参加课程,加入我们的社区,开启您的数据科学和机器学习之旅!

课程评论(0条)

课程详情

Become a complete A.I., Data Scientist and Machine Learning engineer! Join a live online community of 900,000+ engineers and a course taught by industry experts that have actually worked for large companies in places like Silicon Valley and Toronto. Graduates of Andrei's courses are now working at Google, Tesla, Amazon, Apple, IBM, JP Morgan, Meta, + other top tech companies. You will go from zero to mastery!Learn Data Science and Machine Learning from scratch, get hired, and have fun along the way with the most modern, up-to-date Data Science course on Udemy (we use the latest version of Python, Tensorflow 2.0 and other libraries). This course is focused on efficiency: never spend time on confusing, out of date, incomplete Machine Learning tutorials anymore. We are pretty confident that this is the most comprehensive and modern course you will find on the subject anywhere (bold statement, we know).This comprehensive and project based course will introduce you to all of the modern skills of a Data Scientist and along the way, we will build many real world projects to add to your portfolio. You will get access to all the code, workbooks and templates (Jupyter Notebooks) on Github, so that you can put them on your portfolio right away! We believe this course solves the biggest challenge to entering the Data Science and Machine Learning field: having all the necessary resources in one place and learning the latest trends and on the job skills that employers want. The curriculum is going to be very hands on as we walk you from start to finish of becoming a professional Machine Learning and Data Science engineer. The course covers 2 tracks. If you already know programming, you can dive right in and skip the section where we teach you Python from scratch. If you are completely new, we take you from the very beginning and actually teach you Python and how to use it in the real world for our projects. Don't worry, once we go through the basics like Machine Learning 101 and Python, we then get going into advanced topics like Neural Networks, Deep Learning and Transfer Learning so you can get real life practice and be ready for the real world (We show you fully fledged Data Science and Machine Learning projects and give you programming Resources and Cheatsheets)!The topics covered in this course are:- Data Exploration and Visualizations- Neural Networks and Deep Learning- Model Evaluation and Analysis- Python 3- Tensorflow 2.0- Numpy- Scikit-Learn- Data Science and Machine Learning Projects and Workflows- Data Visualization in Python with MatPlotLib and Seaborn- Transfer Learning- Image recognition and classification- Train/Test and cross validation- Supervised Learning: Classification, Regression and Time Series- Decision Trees and Random Forests- Ensemble Learning- Hyperparameter Tuning- Using Pandas Data Frames to solve complex tasks- Use Pandas to handle CSV Files- Deep Learning / Neural Networks with TensorFlow 2.0 and Keras- Using Kaggle and entering Machine Learning competitions- How to present your findings and impress your boss- How to clean and prepare your data for analysis- K Nearest Neighbours- Support Vector Machines- Regression analysis (Linear Regression/Polynomial Regression)- How Hadoop, Apache Spark, Kafka, and Apache Flink are used- Setting up your environment with Conda, MiniConda, and Jupyter Notebooks- Using GPUs with Google ColabBy the end of this course, you will be a complete Data Scientist that can get hired at large companies. We are going to use everything we learn in the course to build professional real world projects like Heart Disease Detection, Bulldozer Price Predictor, Dog Breed Image Classifier, and many more. By the end, you will have a stack of projects you have built that you can show off to others.Here's the truth: Most courses teach you Data Science and do just that. They show you how to get started. But the thing is, you don't know where to go from there or how to build your own projects. Or they show you a lot of code and complex math on the screen, but they don't really explain things well enough for you to go off on your own and solve real life machine learning problems. Whether you are new to programming, or want to level up your Data Science skills, or are coming from a different industry, this course is for you. This course is not about making you just code along without understanding the principles so that when you are done with the course you don't know what to do other than watch another tutorial. No! This course will push you and challenge you to go from an absolute beginner with no Data Science experience, to someone that can go off, forget about Daniel and Andrei, and build their own Data Science and Machine learning workflows. Machine Learning has applications in Business Marketing and Finance, Healthcare, Cybersecurity, Retail, Transportation and Logistics, Agriculture, Internet of Things, Gaming and Entertainment, Patient Diagnosis, Fraud Detection, Anomaly Detection in Manufacturing, Government, Academia/Research, Recommendation Systems and so much more. The skills learned in this course are going to give you a lot of options for your career. You hear statements like Artificial Neural Network, or Artificial Intelligence (AI), and by the end of this course, you will finally understand what these mean!Click "Enroll Now" and join others in our community to get a leg up in the industry, and learn Data Scientist and Machine Learning. We guarantee this is better than any bootcamp or online course out there on the topic. See you inside the course!Taught By:Daniel Bourke:A self-taught Machine Learning Engineer who lives on the internet with an uncurable desire to take long walks and fill up blank pages.My experience in machine learning comes from working at one of Australia's fastest-growing artificial intelligence agencies, Max Kelsen.I've worked on machine learning and data problems across a wide range of industries including healthcare, eCommerce, finance, retail and more.Two of my favourite projects include building a machine learning model to extract information from doctors notes for one of Australia's leading medical research facilities, as well as building a natural language model to assess insurance claims for one of Australia's largest insurance groups.Due to the performance of the natural language model (a model which reads insurance claims and decides which party is at fault), the insurance company were able to reduce their daily assessment load by up to 2,500 claims.My long-term goal is to combine my knowledge of machine learning and my background in nutrition to work towards answering the question "what should I eat?".Aside from building machine learning models on my own, I love writing about and making videos on the process. My articles and videos on machine learning on Medium, personal blog and YouTube have collectively received over 5-million views.I love nothing more than a complicated topic explained in an entertaining and educative matter. I know what it's like to try and learn a new topic, online and on your own. So I pour my soul into making sure my creations are accessible as possible.My modus operandi (a fancy term for my way of doing things) is learning to create and creating to learn. If you know the Japanese word for this concept, please let me know.Questions are always welcome.Andrei Neagoie:Andrei is the instructor of the highest rated Development courses on Udemy as well as one of the fastest growing. His graduates have moved on to work for some of the biggest tech companies around the world like Apple, Google, Amazon, JP Morgan, IBM, UNIQLO etc.He has been working as a senior software developer in Silicon Valley and Toronto for many years, and is now taking all that he has learned, to teach programming skills and to help you discover the amazing career opportunities that being a developer allows in life. Having been a self taught programmer, he understands that there is an overwhelming number of online courses, tutorials and books that are overly verbose and inadequate at teaching proper skills. Most people feel paralyzed and don't know where to start when learning a complex subject matter, or even worse, most people don't have $20,000 to spend on a coding bootcamp. Programming skills should be affordable and open to all. An education material should teach real life skills that are current and they should not waste a student's valuable time. Having learned important lessons from working for Fortune 500 companies, tech startups, to even founding his own business, he is now dedicating 100% of his time to teaching others valuable software development skills in order to take control of their life and work in an exciting industry with infinite possibilities. Andrei promises you that there are no other courses out there as comprehensive and as well explained. He believes that in order to learn anything of value, you need to start with the foundation and develop the roots of the tree. Only from there will you be able to learn concepts and specific skills(leaves) that connect to the foundation. Learning becomes exponential when structured in this way. Taking his experience in educational psychology and coding, Andrei's courses will take you on an understanding of complex subjects that you never thought would be possible. See you inside the course!

课程标签

0人关注该课程

主题相关的课程