Creating dashboards to interpret machine learning model

Explainer Dashboard(Source: By Author)

Nowadays, creating a machine learning model is easy because of different python libraries that are in the market like sklearn, lazypredict, etc. These libraries are easy to use and used to create different types of models along with different types of visualizations and finding out the model performance. If you don’t know how lazy predict works, check out the article given below.

The main challenge nowadays is that models are not interpreted easily which makes it difficult for a non-technical person to understand and interpret the logic and how the model is working.

Explainer dashboard is an open-source python library…


Using Skater to built ML visualization

Tree(Source: By Author)

Interpreting a machine learning model is a difficult task because we need to understand how a model works in the backend, what all parameters the model uses, and how the model is generating the prediction. There are different python libraries that we can use to create machine learning model visualizations and analyze who the model is working.

Staker is an open-source python library that enables machine learning model interpretations for different types of black-box models. It helps us create different types of visualization, making it easier to understand how a model is working.

In this article, we will explore Skater…


Comparing correlation with causation

Photo by Benjamin Behre on Unsplash

Correlation is also known as an association. It refers to a relation between two different entities or data points. When one thing goes up another comes down and vice-versa which means that they change together.

Let’s take an example of an MNC which is studying their sales data for the past 10 years, the data contains the sales of each year in dollars and different features like the amount spent on advertisements through TV, radio, and newspaper.

To understand this data, we created scatter plots and found out that all these features depend linearly and in a positive direction on…


Creating wordcloud using different images

Wordcloud(Source: By Author)

Wordcloud is a visual representation of clusters of words with different sizes according to their times of occurrence in the dataset. The more a word appears larger will be its size in the word cloud. It helps in understanding the sentiments or the occurrence of particular words in a dataset.

Wordcloud is an open-source python library that is used to create wordclouds. In this article, we will be using different images for creating wordclouds on them and also explore different datasets and types of wordcloud.

Let’s get started…

Installing required libraries

We will start by installing the wordcloud using pip. …


Using drawdata to generate fake data

(Source: By Author)

Creating machine learning models helps in understanding the interaction between different columns/data points. It shows us how we can calculate the deviation a data point shows with respect to change in the feature data points.

While learning data science, generally everyone starts learning using the dataset that is already there in the sklearn and is used for ages, but in order to get a better understanding of data correlation and how data behaves in different machine learning models, we need more datasets.

Drawdata is an open-source python library that helps in generating data by…


Using Plotnine for data visualization

(Source: By Author )

Data Visualization is visually representing the data in order to find out certain patterns or outliers. It helps in finding the relation between different attributes of a dataset. It is a graphical representation of data.

Plotnine is an open-source library based on ggplot2 and is an implementation of the grammar of graphics. Creating plots using grammar is easy using plotnine because it makes custom plots easy and can also create simple plots.

In this article, we will learn about how to use plotnine to create different bars and charts.

Let’s get started…

Installing required libraries

We will start by installing the Plotnine using…


Visualizing geographical data using plotly

Source: By Author

Plotly is an open-source library that creates high-level interactive graphs it can be used to plot various types of graphs and charts easily.

Creating a geographical plot has never been so easy before plotly. Plotly uses JS in the backend to render the graphs. Which makes them visually appealing and high interactive.

In this article, we will be using plotly to create geographical plots and use other functionalities as well.

Let’s get started…

Installing required libraries

We will start by installing plotly using pip. The command given below will install it.

pip install plotly

Importing required libraries

In this step, we will import some required libraries…


Generating prediction of the stock for a next business day

Photo by Nick Chong on Unsplash

Predicting stock prices is a difficult task because it takes into account different technical indicators which are different mathematical calculations performed on stock parameters like volume, price, etc. We can use these indicators to identify different patterns that a stock follows but it is very difficult for a normal human being to understand these indicators and make a decision out of these.

Stocker is an open-source python library that can forecast the stock closing price of the next business day. You don't have to understand or go through different technical indicators or news related to stocks just need to pass…


Using lazy predict for creating multiple machine learning models in just 2 lines

Photo by Pietro Jeng on Unsplash

Creating machine learning models and finding out the best model is a tiresome task because it will take a lot of time and effort. Lazy predict helps in building multiple machine learning models in just 2 lines of code.

It not only creates multiple models but also helps in understanding which models work for the given data. So that we can use that model and perform hyperparameter tuning to make it more accurate. It is easy to use and is open source. It creates majorly all the machine learning models for regression and classification.

In this article, we will learn…


Using leather for optimized exploratory charting

Photo by Isaac Smith on Unsplash

Data Visualization plays an important role in data analysis because as soon as the human eyes see some charts or graphs they try finding the patterns in that graph.

Data Visualization is visually representing the data using different plots/graphs/charts to find out the pattern, outliers, and relation between different attributes of a dataset. It is a graphical representation of data.

Leather is an open-source python library used to create scale-independent SVG charts. It can chart whatever data you pass to it. It is developed purely in python and has no other dependencies.

In this article, we will be exploring how…

Himanshu Sharma

An Aspiring Data Scientist passionate about Data Visualization with an Interest in Finance Domain.

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