Python 在数据科学和机器学习中的应用（2024）
- 1 - Introduction
- 1 - Setting up the Environment
- 2 - Introduction to Python Tools
- 2 - Python Crash Course
- 3 - Arithmetic Operations in Python
- 4 - Data Types
- 5 - Variables
- 6 - Intro to Lists
- 7 - Lists 2
- 8 - Lists 3
- 9 - Tuples
- 10 - Strings 1
- 11 - Strings 2
- 12 - Dictionaries
- 13 - Sets
- 3 - Python Pandas
- 14 - Introduction to Pandas
- 15 - Pandas Series Part 1
- 16 - Pandas Series Part 2
- 17 - Pandas Series Unique
- 18 - Pandas Series Sorting
- 19 - Introduction to DataFrames
- 20 - Accessing csv files
- 21 - Data Inspection
- 22 - Dataframe Indexing 1
- 23 - Dataframe Indexing 2
- 24 - Dataframe Filter
- 25 - Position based indexing using iloc
- 26 - Dataframe Slicing using iloc
- 27 - Label based Slicing using loc
- 28 - Loc with numeric index
- 29 - Reset Index
- 30 - Rename Columns
- 31 - Conditional Filter
- 32 - Advanced Filter
- 33 - Missing Values Part 1
- 34 - Missing Values Part 2
- 35 - Group by
- 4 - Data Exploration and Cleaning
- 36 - Intro to Time Series
- 37 - Downloading Data yfinance API
- 38 - String to Datetime
- 39 - Reading Files
- 40 - Working with My Sql Database
- 41 - Slice Time Series Data
- 42 - Pivot DataFrame
- 43 - Resample DataFrame
- 44 - Data Normalization
- 45 - Frequency Tables
- 46 - Visualization Part 1 Pandas
- 47 - Visualization Part 2 Matplotlib
- 5 - Financial Returns
- 48 - Calculate Price Changes
- 49 - Calculate Financial Returns
- 50 - TVPI
- 51 - CAGR
- 52 - Geometric Returns
- 53 - Risk vs Returns
- 54 - Simple vs Compound Interest
- 55 - Continuous Compounding
- 56 - Intro to log Returns
- 57 - Daily Return vs Log Returns
- 58 - More About Log Returns
- 6 - Basic Statistics
- 59 - Descriptive Statistics
- 60 - Five Point Summary
- 61 - Moving Averages
- 62 - Confidence Intervals
- 7 - Inferential Statistics
- 63 - Statistical Distributions
- 64 - Hypothesis Testing
- 65 - Analysis of Variance
- 8 - Predictive Modeling
- 66 - Linear Regression
- 67 - Logistic Regression
- 68 - Decision Trees
- 69 - Random Forests