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In this video, we are going to cover how to do market basket analysis using Python. This video will help you to understand what is market basket analysis, after which will do a hands-on lab demo to do market basket analysis using python.
01:40 What is market basket analysis?
04:30 Hands-on lab demo
Link for the dataset - https://drive.google.com/drive/folders/106IONyudC4vC0Qz7hz13-Z_TCw7Aoeyd?uspsharing
What is market basket analysis?
Retailers utilize market basket analysis, a data mining approach, to boost sales by better understanding client buying patterns. Large data sets, such as purchase histories, must be analyzed to identify product groups and items that are most likely to be bought together.
What is Numpy?
NumPy is a Python library used for working with arrays.It also has functions for working in the domain of linear algebra and matrices. It is an open-source project and you can use it freely. NumPy stands for Numerical Python.
What is Pandas?
Pandas is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series.
What is Matplotlib?
Python scripts can be used to create 2D graphs and plots using the Matplotlib module. With features to control line styles, font attributes, formatting axes, and other features, it offers a module called plot that makes things simple for plotting.
What is Seaborn?
An open-source Python library based on matplotlib is called Seaborn. It is utilized for data exploration and data visualization. With data frames and the Pandas library, Seaborn functions with ease
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About Post Graduate Program In AI And Machine Learning
This AI ML course is designed to enhance your career in AI and ML by demystifying concepts like machine learning, deep learning, NLP, computer vision, reinforcement learning, and more. You'll also have access to 4 live sessions, led by industry experts, covering the latest advancements in AI such as generative modeling, ChatGPT, OpenAI, and chatbots.
Key Features
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Skills Covered
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- Generative Modeling
- Statistics
- Python
- Supervised Learning
- Unsupervised Learning
- NLP
- Neural Networks
- Computer Vision
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