4.55 de 5
4.55
22 reseñas sobre Udemy

Data Mining for Business in Python 2021

9 Data Mining algorithms for Data Science, Machine Learning and Explainable Artificial Intelligence. 18 Case Studies.
Instructor:
Diogo Alves de Resende
262 estudiantes matriculados
English [Auto]
Survival Analysis
Cox Proportional Hazard Regression
CHAID
Cluster Analysis - Gaussian Mixture Model
Association Rule Learning
Random Forest
LIME
SHAP
Data Mining
Principal Component Analyisis
XGBoost
Manifold Learning

Are you looking to learn how to do Data Mining like a pro? You have come to the right place.

Welcome to the most exciting Data Mining course in Python. I will show you the most impactful algorithms that I have witnessed in my professional career to derive meaningful insights.

In the age of endless spreadsheets, it is easy to feel overwhelmed with so much data. This is where Data Mining techniques come in. To swiftly analyze, find patterns, and deliver an outcome to you. For me, the Data Mining value added is that you stop the number crunching and pivot table creation, leaving time to come with actionable plans based on the insights.

Now, why should you enroll in the course? Let me give you four reasons.

The first is that you will learn the models’ intuition without focusing too much on the math. It is crucial that you know why a model makes sense and the underlying assumptions behind it. I will explain to you each model using words, graphs, and metaphors, leaving math and the Greek alphabet to the bare minimum.

The second reason is the thorough course structure of the most impactful Data Mining techniques. Based on my experience, the course curriculum has the algorithms I believe to be most impactful, up-to-date, and sought after. Here is the list of the algorithms we will learn:

Supervised Learning

  • Survival Analysis

  • Cox Proportional Hazard Regression

  • CHAID

Unsupervised Learning

  • Cluster Analysis – Gaussian Mixture Model

  • Dimension Reduction – PCA and Manifold Learning

  • Association Rule Learning

· Explainable Artificial Intelligence

  • Random Forest and Feature Importance

  • LIME

  • XGBoost and SHAP

The third reason is that we code together, line by line. Programming is challenging, especially for beginners. I will guide you through every code snippet. I will also explain all parameters and functions that you need to use, step by step. In the end, you will have code templates ready to use in your problems.

The final reason is that you practice, practice, practice. At the end of each section, there is a challenge. The goal is that you apply immediately what you have learned. I give you a dataset and a list of actions you need to take to solve it. I think it is the best way to really cement all the techniques in you. Hence, there will be 2 case studies per technique.

I hope to have spiked your interest, and I am looking forward to seeing you inside!

Share it with friends
You can view and review the lecture materials indefinitely, like an on-demand channel.
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
4.6
4.6 de 5
Calificaciones 22

Calificación Detallada

5 estrellas
17
4 estrellas
1
3 estrellas
0
2 estrellas
0
1 estrellas
0
e0b0722fe2cb40b5e6b89b9177ff2710
Garantía de devolución de dinero de 30 días

Incluye

9 horas de video a pedido
3 artículos
Acceso completo de por vida
Acceso en el móvil y en la televisión
Certificado de finalización
Data Mining for Business in Python 2021