Data Mining for Business in Python 2021

欢迎来到最激动人心的Python数据挖掘课程。我将向您展示我在职业生涯中目睹的最有影响力的算法，以得出有意义的见解。

在电子表格层出不穷的时代，如此多的数据容易让人感到不知所措。这就是数据挖掘技术的用武之地。快速分析，发现模式并为您提供结果。对我来说，数据挖掘的价值在于，您可以停止数字运算和数据透视表的创建，从而可以留出时间根据洞察力制定可行的计划。

现在，为什么要注册该课程？让我给你四个理由。

首先，您将学习模型的直觉，而不必过多地关注数学。了解模型为何有意义以及其背后的基本假设至关重要。我将使用单词，图表和隐喻向您解释每个模型，而数学和希腊字母则保持最低限度。

第二个原因是最有影响力的数据挖掘技术的全面课程结构。根据我的经验，该课程课程具有我认为最有影响力，最新且最受欢迎的算法。

MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 137 lectures (8h 51m) | Size: 2.62 GB
9 Data Mining algorithms for Data Science, Machine Learning and Explainable Artificial Intelligence. 18 Case Studies

What you’ll learn:
Survival Analysis
Cox Proportional Hazard Regression
CHAID
Cluster Analysis – Gaussian Mixture Model
Rule Learning Association
Random Forest
LIME
SHAP
Data Mining
Principal Component Analysis
XGBoost
Manifold Learning

Requirements
Statistics – Linear and Logistic Regression
Basic Python

Description
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 y ou 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

Rule Learning Association

· 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!

Who this course is for
People looking to learn Data Mining algorithms