Bollinger Bands Algorithm – Python Binance API for Crypto Trading

A Bollinger Band consists of three lines: a simple moving average, an upper band, and a lower band. The assumption is that if the real price crosses over one of the bands, this can be seen as a signal to trade in or our of a given asset. For cryptocurrencies, breakout trades are more frequently … Read more

Moving Average Convergence Divergence (MACD) – Python Binance API for Crypto Trading

MACD is a trend-following momentum indicator used for trading. It consists of two lines: The MACD line is calculated by taking the difference between short-term EMA and long-term EMA. Exponential Moving Average (EMA) assigns weights to all the values due to a given factor whereas the latest data point gets the maximum weight, and the … Read more

NumPy Sort [Ultimate Guide]

The np.sort(array) function returns a sorted copy of the specified NumPy array. Per default, it sorts the values in ascending order, so np.sort([42, 2, 21]) returns the NumPy array [2 21 42]. Here’s an example of 1D sorting: And here’s an example of 2D sorting — each axis is sorted separately. An example of 3D … Read more

[Cheat Sheet] 6 Pillar Machine Learning Algorithms

This machine learning cheat sheet gives you a visual overview of 6 must-know machine learning algorithms (and where to learn more). Linear Regression: train your linear model to predict output values. K-Means Clustering: apply it on unlabeled data to find clusters and patterns in your data. K-Nearest Neighbors: use a similarity metric to find the … Read more

Logistic Regression in Python Scikit-Learn

Logistic regression is a popular algorithm for classification problems (despite its name indicating that it is a “regression” algorithm). It belongs to one of the most important algorithms in the machine learning space. Linear Regression Background Let’s review linear regression. Given the training data, we compute a line that fits this training data so that … Read more

Random Forest Classifier with sklearn

Does your model’s prediction accuracy suck but you need to meet the deadline at all costs? Try the quick and dirty “meta-learning” approach called ensemble learning. In this article, you’ll learn about a specific ensemble learning technique called random forests that combines the predictions (or classifications) of multiple machine learning algorithms. In many cases, it … Read more

SVM sklearn: Python Support Vector Machines Made Simple

Support Vector Machines (SVM) have gained huge popularity in recent years. The reason is their robust classification performance – even in high-dimensional spaces: SVMs even work if there are more dimensions (features) than data items. This is unusual for classification algorithms because of the curse of dimensionality – with increasing dimensionality, data becomes extremely sparse … Read more

Python Scikit-Learn Decision Tree [Video + Blog]

Decision Trees are powerful and intuitive tools in your machine learning toolbelt. Decision trees are human-readable – in contrast to most other machine learning techniques. You can easily train a decision tree and show it to your supervisors who do not need to know anything about machine learning in order to understand how your model … Read more