## Breadth-First Search (BFS) Algorithm in Python

What is a Graph? When we want to illustrate how one thing relates to another, most often, we would preferably use a graph. From a concrete perspective, a graph is a graphical representation or an image of relationships. A graph is built of entities and their relationships. Entities represent actors in a relationship you are … Read more

## The Quickselect Algorithm – A Simple Guide with Video

What is the Quickselect algorithm? The Quickselect algorithm is a computer algorithm designed to find the kth (e.g. smallest or largest) element from an unordered list. It is based on the idea behind the Quicksort algorithm, invented by the same author, Sir Charles Anthony Richard (Tony) Hoare. Here, k stands for the index of an … Read more

## 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

## Simple Moving Average (SMA) – Python Binance API for Crypto Trading

A simple moving average (SMA) is calculated by summing over a fixed number of last prices, say k, and dividing this by the number of prices k. Depending on the selection k, you can obtain short-term or long-term SMAs. Short-term SMAs respond quickly whereas long-term SMAs respond slowly to changes in the prices. You can … 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

Disclaimer: The bot built here should be used only as a learning tool. If you choose to do real trading on Binance, then you have to build your own criteria and logic for trading. The author is not responsible for any losses incurred if you choose to use the code developed here on Binance. Note: … 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