Data Science & Deep Learning for Business™ 20 Case Studies
Use Python to solve problems in Retail, Marketing, Product Recommendation, Customer Clustering, NLP, Forecasting & more!
4.44 (1051 reviews)
11,552
students
21 hours
content
Nov 2021
last update
$64.99
regular price
What you will learn
Understand the value of data for business
Solve common business problems in Marketing, Sales, Customer Clustering, Banking, Real Estate, Insurance, Travel and more!
Python, Pandas, Matplotlib & Seaborn, SkLearn, Keras, Tensorflow, NLTK, Prophet, PySpark, MLLib and more!
Machine Learning from Linear Regressions (polynomial & multivariate), K-NNs, Logistic Regressions, SVMs, Decision Trees & Random Forests
Unsupervised Machine Learning with K-Means, Mean-Shift, DBSCAN, EM with GMMs, PCA and t-SNE
Build a Product Recommendation Tool using collaborative & item/content based
Hypothesis Testing and A/B Testing - Understand t-tests and p values
Natural Langauge Processing - Summarize Reviews, Sentiment Analysis on Airline Tweets & Spam Detection
To use Google Colab's iPython notebooks for fast, relaible cloud based data science work
Deploy your Machine Learning Models on the cloud using AWS
Advanced Pandas techniques from Vectorizing to Parallel Processsng
Statistical Theory, Probability Theory, Distributions, Exploratory Data Analysis
Predicting Employee Churn, Insurance Premiums, Airbnb prices, credit card fraud and who to target for donations
Big Data skills using PySpark for Data Manipulation and Machine Learning
Cluster customers based on Exploratory Data Analysis, then using K-Means to detect customer segments
Build a Stock Trading Bot using re-inforement learning
Apply Data Science & Analytics to Retail, performing segementation, analyzing trends, determining valuable customers and more!
How to apply Data Science in Marketing to improve Conversion Rates, Predict Engagement and Customer Life Time Value
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2302640
udemy ID
4/2/2019
course created date
11/28/2019
course indexed date
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