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analyzing-social-media

Analyzing Social Media Data in Python

blueconic_webhook

Blueconic Webhook connection to receive and send data to server side GTM

building-statsmodel-with-python

A statistical model is a mathematical model that embodies a set of statistical assumptions concerning the generation of some sample data and similar data from a larger population. A statistical model represents, often in considerably idealized form, the data-generating process.

coach

Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms

conversation-ai

This repository is about conversation AI using Eleven labs and ChatGPT4

course-info

Syllabus for INF1005H and INF1006H - Social Data Analytics, Winter 2018

customer-analytics-a-b-testing

The most successful companies today are the ones that know their customers so well that they can anticipate their needs. Customer analytics and in particular A/B Testing are crucial parts of leveraging quantitative know-how to help make business decisions that generate value.

customer-segmentation

you will run cohort analysis to understand customer trends. On top of that, you will learn how to build easy to interpret customer segments. Finally, you will make your segments more powerful with k-means clustering, in just few lines of code! By the end of this , you will be able to apply practical customer behavioral analytics and segmentation techniques.

data-layer-helper

JavaScript library for working with dataLayer message queues.

deep-learning-v2-pytorch

Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

deeprl

ShangtongZhang/DeepRL

dltfpt

Deep Learning with TensorFlow, Keras, and PyTorch by Jon Krohn

dltfpt-1

Deep Learning with TensorFlow, Keras, and PyTorch

dm_alchemy

DeepMind Alchemy task environment: a meta-reinforcement learning benchmark

dopamine

Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.

ecommerce-analytics

The Ecommerce reports allow you to analyze purchase activity on your site or app. You can see product and transaction information, average order value, ecommerce conversion rate, time to purchase, and other data.

examples

TensorFlow examples

experience-platform-postman-samples

financial-concepts-in-python

Understanding the basic principles of finance is essential for making important financial decisions ranging from taking out a student loan to constructing an investment portfolio. Combining basic financial knowledge with Python will allow you to construct some very powerful tools. All understanding about the time value of money, how to compare potential projects and how to make rational, data-driven financial decisions.

financial-data-management

Data on companies listed on the stock exchanges NASDAQ, NYSE, and AMEX with information on company name, stock symbol, last market capitalization and price, sector or industry group, and IPO year.

fuel_economy_analysis

Data on cars used for testing fuel economy

fullstack-nanodegree-vm

functional_intro_to_python

[tutorial]A functional, Data Science focused introduction to Python

ga4-ecommerce-analytics

This is GA4 Ecommerce analytics code for Google Tag manager

galeria

Udacity Gallery app for student use on Deploying Applications with Heroku course.

generative-ai

Sample code and notebooks for Generative AI on Google Cloud

google-research

Google AI Research

image-processing-in-scikit-learn-

Similar to pickling things, we have to pay attention to the right preservatives. Of course, mobile phone also provide us with a range of image processing software, but as soon as we need to manipulate a huge quantity of photographs we need other tools. This is when programming and Python comes into play. Python and its modules like Numpy, Scipy, Matplotlib and other special modules provide the optimal functionality to be able to cope with the flood of pictures.

improvedgan-pytorch

Semi-supervised GAN in "Improved Techniques for Training GANs"

keras-gan

Keras implementations of Generative Adversarial Networks.