Python machine learning-sklearn digging breast cancer cells

Python machine learning-sklearn digging breast cancer cells (Bo Master personally recorded)

Https://study.163.com/course/introduction.htm?courseId=1005269003&utm_campaign=commission&utm_source= Cp-400000000398149&utm_medium=share

Course Overview

Toby, a licensed financial company as a model validation expert, the largest data mining department in the domestic medical data center head! This course explains how to use Python's sklearn to quickly build machine learning models. This course combines the clinical data of breast cancer cells in Wisconsin and the practice exercises to establish a predictive classifier for cancer cells.

This video series is easy to understand and is designed for students and research institutions, Python enthusiasts.
This video tutorial series has full Python code, and viewers can download the actual operation after viewing it.

Understand the basic knowledge of cancer oncology, establish a healthy lifestyle, prevent cancer and reduce the cost of cancer treatment.

Top Ten Classic machine learning algorithms in the course: Logistic regression, support vector, KNN, neural network, random forest, xgboost,lightgbm,catboost. The course provides video-based scripting, which can be used in various areas of data, including financial anti-fraud models, credit scoring models, revenue forecasting models, and so on to provide ready-made solutions for SMEs.

Visualization of random forest variable weights

The course takes three years, 360 degrees without dead angle to tell the whole model development cycle, non-market fast food teaching. Tutorials include data acquisition, data preprocessing, variable filtering, model screening, model evaluation, and model tuning.

This video series is easy to understand and is designed for students and research institutions, Python enthusiasts. This video tutorial series has full Python code, and viewers can download the actual operation after viewing it. These model codes provide solutions for small and midsize businesses.

anaconda+knn+ Network style parameter + cross validation

Directory

Chapter 1: Cancer common sense

Lesson 1 alarm bells ringing! The cancer is right next to you. 11:00

Lesson 2 Cancer Science Introduction 23:05

Lesson 3 viral bacteria-induced cancer 20:43

4 Lessons from mouth-cancer food disclosure 08:37

Lesson 5Python machine learning to dig cancer cells Overview 13:11

Chapter 2:sklearn Programming Environment Construction

Lesson 6Python Unofficial Expansion Pack 02:21

Lesson 7python third-party Package installation (PIP and Conda install) 02:48

Lesson 8Anaconda Download Install 07:02

Lesson 9Canopy Download and install 03:47

Chapter 3:sklearn Machine Learning Basics

Lesson 10 Introduction to Machine learning Database 02:19

Lesson 11 machine Learning Books recommended 02:59

Lesson 12Python Data Science Common package 13:14

Lesson 13 How to choose a model 03:57

Class 14sklearn algorithm quick check table 02:29

Lesson 15sklearn Modeling Basic Code 18:19

Lesson 16python Introduction to Data Science (elective) 55:15

Chapter 4: Access to breast cancer clinical data

Lesson 17 Data Acquisition-breast cancer cell clinical Data 07:06

Chapter 5: Variable Filtering and descriptive statistics

Lesson 18 factor Analysis-Interpreting cancer cell characteristics 33:24

Lesson 19 Variable Filtering 1-model method 11:50

Lesson 20 variable Screening 2-proportional method percentile07:04

Lesson 21 Variable Filtering 3-variance method (recommended) 06:36

Lesson 22 Variable Screening 4-kbest01:59

Chapter 6: Ten Classic machine learning algorithms-building a breast cancer cell classifier

Lesson 23 Logistic Regression Regression27:17

Lesson 24 Support Vector svm13:48

Class 25KNN nearest neighbor algorithm 13:38

Lesson 26 Decision Tree-decision tree21:59

Lesson 27 Random Forest-random forest14:02

Lesson 28 Neural Network Neural network17:07

Lesson 29xgboost12:27

Lesson 30LIGHTGBM03:51

Lesson 31CATBOOST07:08

Lesson 32 Algorithm Comparison 10:52

Lesson 33bagging VS boosting05:51

Chapter 7: Data preprocessing

Lesson 34PANDASL Data Processing Fundamentals 15:50

Lesson 35 dummy Variable handling-hotcode thermal code 06:14

Lesson 36imputer-missing Data processing 04:49

Class 37scale-Data Standard processing 12:13

Chapter 8: Model Assistant

38-Time Calendar Adjustment method 05:15

Lesson 39 Network Style parameter 106:10

Lesson 40 Network Style parameter 204:26

Lesson 41 Random Net style parameter 02:29

Chapter 9: Model Validation

Lesson 42 cross-validation crosses validation03:45

Lesson 43 Model Verification Preface 12:15

Lesson 44 Confusion Matrix 14:16

Lesson 45ROC Curve 11:57

Lesson 46PSI (population stability Index) 10:20

Lesson 47 Gini coefficient Gini index25:16

Lesson 48KS (Kolmogorov-smirnoff) 06:51

Chapter 10: Appendix

Lesson 49 Video Tutorial python script download URL need to buy watch

Lesson 50 cancer cells under microscope

Python machine learning-sklearn digging breast cancer cells