Data Driven Dealings Development: Analysing, Predicting, and Recommending sales items per customer using Machine Learning Models with Python. - Tapa blanda

Sinopsis

When I was starting my Python data analysis journey I was missing books or tutorials which really cover all the topics involved when trying to conduct a sales analysis successfully. Especially when you are a complete newbie conducting an analysis from A-Z without any (or not sufficient) pre-knowledge is difficult, because most books only cover specific parts of the whole project, and it is challenging to put all the pieces of the puzzle together. That is my main motivation for writing this book: you to have one guideline in hand which leads all the way through your whole sales analysis project, from installing all the necessary Python libraries, cleaning the data, effectively training the Machine Learning (ML) models and deploying the results to your colleagues in an intelligible way. The topics covered in this book are: Explorative Data Analysis (EDA)Feature Engineering and Clustering (Unsupervised Machine Learning) Predicting of future sales using statistical modelling, Prophet, and Long-Short-Term Memory (LSTM) using deep learning techniques (Tensorflow/ Keras) Market Basket Analysis using the Apriori Algorithm and Spark Recommend products to our customers using Scikit-Learn, Pandas,Tensorflow, and Turicreate Stack

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