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Power-Prediction-LSTM
Short-Term Power Forecasting Using LSTMs and Linear RegressionConsumer-Complaint-Classification
Customer Complaint Classification using Generalized multiclass classification using SVM and Logistic RegressorAnalyzing-Visualizing-Data-PowerBI-Solution
# Analyzing-Visualizing-Data-PowerBI ![Analyzing-Visualizing-Data-PowerBI](https://www.edx.org/sites/default/files/course/image/promoted/dat207x-course_card_image11122015-378x225.png) This repository contains the lab files and other resources for the free Microsoft course DAT207x: Analyzing and Visualizing Data with Power BI. To learn how to connect, explore, and visualize data with Power BI, sign up for this course on [edX](https://www.edx.org/course/analyzing-visualizing-data-power-bi-microsoft-dat207x). ## DataSet / Examples Terms of Usage and Disclaimer Throughout the course you will use examples and datasets provided through text files, Excel workbooks, SQL backup, and Access database. They are provided "as-is." Information and views expressed in the workbooks, including URL and other Internet Web site references, may change without notice. You bear the risk of using it. Some examples are for illustration only and are fictitious. No real association is intended or inferred. Microsoft makes no warranties, express or implied, with respect to the information provided here. These datasets/examples do not provide you with any legal rights to any intellectual property in any Microsoft product. You may copy and use these resources for your internal, reference purposes. The workbooks and related data are provided by [obviEnce](www.obvience.com). ObviEnce is an ISV and an Intellectual Property (IP) Incubator focused on Microsoft Business Intelligence. ObviEnce works closely with Microsoft to develop best practices and thought leadership for jump-starting and deploying Microsoft Business Intelligence solutions. The workbooks and data are property of obviEnce, LLC and have been shared solely for the purpose of demonstrating Power BI functionality with industry sample data. Any uses of the workbooks and/or data must include the above attribution (that is also on the Info worksheet included with each workbook). The workbook and any visualizations must be accompanied by the following copyright notice: obviEnce Β©. By clicking any of the links to download the files, you are agreeing to the terms above. ###Important All the data you need for this course is providMovie-Recommendation
Recommedation of movies to a user based on user rating data.Restaurant-Forecasting
Predict top 'Menu Item' and 'Item Qty' for lunch and dinner. These predictions need to be for future dates (Monday to Sunday, July 1st to July 7th)Voice-Assistent-Calendar-Application
Automating Calendar Application through your personal assistent BotCredit_Risk_Customer_Prediction
IntroToDeepForwardNetwork
Deep Forward Architecture From ScratchCapstone_DS
In this Capstone Project challenge, you will put into practice some of the key principles and techniques you have learned in Machine Learning with PythonAQI_Prediction
DataScience_AI_Labs
We have added all the data science and Artificial Intelligence practical labs with enough theory and able to understand. All the content are more precise and informative to all the Date scientist profecient and fresh learners. Alo added capstone project and course to sharpen your skills.BabyStore
Hackerrank-Practice-Python
Python practice problems and solutionsIRIS_Dataset
Classify the species of iris flowers on IRIS Dataset, given measurement of flower characteristicsUnsupervised_Machine_Learning
Introduction to Unsupervised Machine Learning, number of approaches to unsupervised learning such as K-means clustering, hierarchical agglomerative Clustering and its applications.Love Open Source and this site? Check out how you can help us