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所在平台: Udemy |
课程主页: https://www.udemy.com/course/kaggle-masterclass/
课程评论：没有评论
课程名称：Kaggle大师班 - 建立机器学习项目集 课程概述：本职业导向的硕士班旨在通过“实践出真知”的方法，使您在数据科学领域获得深入的实践经验。构建项目集是顺利找到理想工作的最佳方式，而Kaggle是数据科学家的最佳平台！多年来，Kaggle已成为数据科学家社区中最受欢迎的平台，除了帮助您学习新技能和应用新技术，它在您的职业生涯中也发挥了至关重要的作用。 本课程将为您提供与多种项目的深入实践经验，这些项目包含成为熟练数据科学家的必要组成部分。通过完成课程中的项目，您将获得关于以下内容的实践经验，并拥有一系列项目以反映您的学习成果： - 使用NumPy和Pandas进行数据分析和数据整理 - 使用Matplotlib和Seaborn进行探索性数据分析 - 使用Scikit Learn进行机器学习 - 使用TensorFlow进行深度学习 - 使用Facebook Prophet进行时间序列预测 - 使用Scikit-Time进行时间序列预测 本课程主要关注通过构建包含一系列使用Kaggle平台上竞争和公共数据集的Python Jupyter Notebook项目集，帮助您脱颖而出。您将设置自己的Kaggle个人资料，以便在未来的就业机会中脱颖而出。
This career-ready Masterclass is designed to help you gain hands-on and in-depth exposure to the domain of Data Science by adopting the learn by doing approach. And the best way to land your dream job is to build a portfolio of projects. And the best platform for a Data Scientist is Kaggle! Over the years, Kaggle has become the most popular community for Data Scientists. Kaggle not only helps you learn new skills and apply new techniques, but it now plays a crucial role in your career as a Data Professional. This course will give you in-depth hands-on experience with a variety of projects that include the necessary components to become a proficient data scientist. By completing the projects in this course, you will gain hands-on experience with these components and have a set of projects to reflect what you have learned. These components include the following:Data Analysis and Wrangling using NumPy and Pandas.Exploratory Data Analysis using Matplotlib and Seaborn.Machine Learning using Scikit Learn.Deep Learning using TensorFlow.Time Series Forecasting using Facebook Prophet.Time Series Forecasting using Scikit-Time.This course primarily focuses on helping you stand out by building a portfolio comprising of a series of Jupyter Notebooks in Python that utilizes Competitions and Public Datasets hosted on the Kaggle platform. You will set up your Kaggle profile that will help you stand out for future employment opportunities.
