Python

Python is an interpreted, high-level and general-purpose programming language. It supports multiple programming paradigms, including structured (particularly, procedural), object-oriented, and functional programming. A lot of machine learning and deep learning libraries are running in Python nowadays.

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DataScience
Python

3 ways to do dimensionality reduction techniques in Scikit-learn

Dimensionality reduction techniques are used to extract informative features that could be used for later learning, etc. Tested PCA, MDS and t-SNE for the breast cancer dataset.

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DataScience
Python
Statistics

Scikit-learn LinearRegression vs Numpy Polyfit

What are differences between linear regression and polynomial regression? We must know these techniques well but it is still vague somewhat.

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DataScience
Python
Statistics

What are standarization and normalization? Test with iris data set in Scikit-learn

Standarization and normalization are essential techniques to apply your data set before using classifiers in some cases. I tested both with iris data set.

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Python
Statistics

3 ways to do test of normality with Scipy library in Python

This is the rough guide how to do test of normality for dataset by leveraging Scipy library. I used probplot, the Shapiro-Wilk test and skewness, kurtosis.

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Crypto
DataScience
Python

Coefficient of variation to compare your crypto assets

This guide shows how to obtain crypto data via CoinGecko API and calculate the coefficient of variation that is a statistical measure of the dispersion of data points.

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AWS
Python

Post an image tweet with Lambda when S3 event triggered

A lambda function guide with Python 3.7 runtime. The function can be triggered by S3 put event and downloaded image will be posted in Twitter.

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Crypto
Python

How to obtain crypto execution prices via WebSocket

Crypto exchanges offer realtime endpoint via WebSocket for rates, orderbooks and executions, etc. This article is a guide how to collect such information in Python.

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DataScience
Python

DiCE -ML models with counterfactual explanations for the sunk Titanic data-

This article is an overview why counterfactual explanations are required in recent ML projects and how to apply Microsoft research DiCE library for Titatic data set. There have been some foreseen and ongoing trends in AI/ML for 2020 such as AutoML, MLOps, AI ethic those are to democratize AI/ML in the industries more than ever. […]

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DataScience
Python

How to draw support and resistence lines with DataFrame in Python

Support and resistence lines are referred to analyze chart patterns, and a direction of assets for traders. This is a guide to draw those lines in matplotlib.

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DataScience
Python

How to draw a trend line with DataFrame in Python

Talib library doesn’t support to draw trendlines. This is the article how to compute trendlines from DataFrame and draw it in matplotlib.

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