Gain insights into predicting retail sales with TensorFlow. Delve into data analysis, training models, and extracting insights using industry techniques. Explore efficient model evaluation with experts from top tech companies.

APLCS.tar.gz

case-study

In this course, you'll work on an industry-level machine learning project based on predicting weekly retail sales given different factors. You will learn the most efficient techniques used to train and evaluate scalable machine learning models. After completing this course, you will be able to take on industry-level machine learning projects, from data analysis to creating efficient models and providing results and insights.

The code for this course is built around the TensorFlow framework, which is one of the premier frameworks for industry machine learning, and the Python pandas library for data analysis. Basic knowledge of Python and TensorFlow are prerequisites. To get some experience with TensorFlow, try our course: Machine Learning for Software Engineers.

This course was created by AdaptiLab, a company specializing in evaluating, sourcing, and upskilling enterprise machine learning talent. It is built in collaboration with industry machine learning experts from Google, Microsoft, Amazon, and Apple.

Applied Machine Learning: Industry Case Study with TensorFlow

# Chapter Goals:
- Analyze plots of the dataset's features with respect to weekly sales and usage in a machine learning model


# A. Analyzing within context

After creating the dataset plots, we should analyze them to determine whether they're useful in the context of our problem. For us, this means deciding whether there's enough correlation between the dataset features and weekly sales to train a machine learning model.

The main thing we're looking for in the plots is non-uniform distributions. A uniform distribution means that the weekly sales are identical regardless of the data feature's value. A non-uniform distribution, such as a normal distribution or a multi-modal distribution, shows that the dataset feature can potentially be used by a machine learning model to predict the sales.

Interpret scatter and bar plots in the context of the project.

What you'll learn from this course

Preliminary Data Analysis

Data Processing

Model Predictions

Interpreting Plots

Chapter Goals:

A. Analyzing within context