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Exposing Bias in IRS Audits Using Python and Plotly Express

 Python in Plain English

According to IRS chief Charles Rettig, the US Treasury loses $1 trillion in unpaid taxes every year. Most of these unpaid taxes are the result of evasion by the wealthy and large corporations. To addr...

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Why Machine Learning Is Not Made for Causal Estimation

 Towards Data Science

Predictive vs. causal inference: a critical distinction Image by author, generated with Dall-E 3. “If all you have is a hammer, everything looks like a nail.” In the era of AI/ML, Machine Learning is...

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Parquet File Format: Everything You Need to Know

 Towards Data Science

With the amounts of data growing exponentially in the last few years, one of the biggest challenges became finding the most optimal way to store various data flavors. Unlike in the (not so far) past, ...

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Learn Python

▶️ Basic Functions
Syntax | Variables | Conditions | Data Types | Numbers | Strings | Formatting | Operators | Generators | Decorators | Functions | Lists | Tuples | Sets | Dictionaries | Parameters | Arguments | Arrays | Linked Lists | Hash Tables | Binary Search Trees | Recursion | Sorting Algorithms | Exception Handling | Serialization 

🚀 Advanced Functions
RegEx | Decorators | Lambdas | Iterators | Classes | Inheritance | Methods | List Comprehensions | Generator Expressions | PyPi | PIP | Conda

💠 Frameworks
Django | Flask | CherryPy | Bottle | Dash | | PyTest | Scrapy | PyScript

🗂 Libraries
TensorFlow | Scikit-Learn | Numpy | Keras | PyTorch | SciPy | Pandas | Theano | Seaborn | OpenCV | Bokeh | Matplotlib | Plotly | BeautifulSoup | SymPy | Pillow

🧰 Other Tools
Selenium | PyCharm | PyTest | Jupyter Notebook | FakerPyGame | Tkinter 

 

Learn Data Science

▶️ Basics
Linear Algebra | Databases | Tabular Data | Time Series | Extract, Transform, Load | Data Formats | Regular Expressions | Important libraries |

💻 Programming languages for Data Science
SQL | R | Python

🐍 Python for Data Science
Syntax | Variables | Data Types | Functions | Numbers | Operators | Important libraries

🔁 Data Sources
Data Mining | Web scraping | Public Data Sets

📊 Exploratory Data Analysis
Principal Component Analysis | Dimensionality Reduction | Normalization | Data Cleaning | Estimators | Feature Extraction | Sampling

🔢 Statistics
Probability Theory | Continuous Distribution | Summary Statistics | Estimation | Hypothesis Testing | Confidence Interval | Monte Carlo Methods

📈 Data Visualization + tools
Storytelling | Charts | Dashboards | Power BI | Tableau | R | Dash | Seaborn | Matplotlib | Bokeh | Plotly

 

Learn Machine Learning

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