✳️Download the Notes & Data Set - [ Ссылка ]
Join us for an in-depth data science project where we analyze Zomato's data to uncover valuable insights and trends. This comprehensive tutorial will guide you through each step of the data analysis process.
Timestamps
00:00 - 02:27 - Introduction
02:28 - 08:12 - Understanding the Business Problems
08:13 - 15:18 - Uploading the DataSet and importing the libraries
15:19 -24:45 - Data Cleaning & Data Preprocessing
24:46 - 25:48 - Question 1 Solution & Count Plot
25:49 - 31:28 - Question 2 Solution & Line Graph
31:29 - 35:29 - Question 3 Solution & Histogram Plot
35:30 - 40:08 - Question 4 Solution & Bar Graph
40:09 - 42:53 - Question 5 Solution & Box Plot
45:54 - 48:40- Question 6 Solution & Heatmap
48:41 - 50:07 - Free Courses of Data Science & Data Analytics
Free Course Data Science - [ Ссылка ]
Free Course Data Analytics - [ Ссылка ]
📊 Introduction to the Project: Get an overview of the Zomato data analysis project and its objectives.
🛠️ Data Collection: Learn how to gather and preprocess the Zomato dataset for analysis.
🔍 Exploratory Data Analysis (EDA): Dive into EDA techniques to understand the dataset, identify patterns, and detect anomalies.
📈 Data Visualization: Discover how to create insightful visualizations to effectively communicate your findings.
📊 Statistical Analysis: Apply statistical methods to analyze the data and extract meaningful insights.
🤖 Machine Learning Models: Build and evaluate machine learning models to predict key metrics and trends.
🔗 Real-World Applications: Understand the practical applications of your analysis in the food and restaurant industry.
📝 Project Summary: Summarize the findings and insights gained from the analysis.
✨ Kickstart your career in a Data Analyst. Apply today! - [ Ссылка ]
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📱 For Any Further Query or Doubts? Contact- 7880-113-112 (Student Helpline Number)
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By the end of this tutorial, you will have a complete understanding of how to conduct a data science project from start to finish, using Zomato data as a case study. Don’t forget to like, comment, and subscribe for more data science projects and tutorials!
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