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 MLJAR-Supervised for Automating EDA Machine Learning Models and Creating Markdown Reports

Source: By Author

Exploratory Data Analysis is an important step for understanding the data that we are working on it helps us in identifying any hidden pattern in the data, the correlation between different columns of the data, and in analyzing the properties of the data. EDA generally takes around 30% of the total project time because we need to write a lot of code in order to create different types of visualizations and analyzing them.

Python provides N number of libraries which helps in automating the process of EDA which in turn saves time and effort but how to choose which library…


Using Optunity for Hyperparameter Optimization of ML Models

Photo by Shahadat Rahman on Unsplash

Hyperparameter tuning is an important task for any model whether it is Machine Learning or Deep Learning because it not only helps in optimizing the models but also helps in getting a higher accuracy and better performance.

There are different Python libraries that help in hyperparameter optimization but most of them are time-consuming or not that efficient. Optunity is an open-source Python library that helps in automating the process of hyperparameter tuning.

In this article, we will explore some of the functionalities that Optunity provides.

Let’s get started…

Installing required libraries

We will start by installing the Optunity library by using pip. …


Using MLBox For Creating Highly Optimized Machine Learning Models

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Creating a Machine Learning model is not a difficult task because Python provides ample libraries which can help in creating models related to problems like Regression, Classification, etc. Python packages like Sklearn Statsmodel can be used for creating these models but the difficult part is optimizing and generalizing these models so that they work on unseen data also.

In other words, creating a Machine Learning model alone does not solve the problem, we should also be able to tune the hyperparameter of these models to make it generalized and achieve higher performance and accuracy. There are a large number of…


Using PMDArima for Time Series Forecasting

PMDArima(Source: By Author)

Time-series forecasting is one of the important applications for Machine Learning and Deep Learning. There are multiple models which can be used for time series forecasting like Arima, Prophet, Holt-Winters, etc. Multiple Python libraries can be used for loading these models and using them but they are not user-friendly and are difficult to use.

PMDArima is an open-source Python library that is used for time series forecasting and also helps in creating time series plots. It is easy to use and generates time-series forecast on the ARIMA model.

In this article, we will explore…


Using Mitosheet for Automating EDA Process

Source: By Author

Exploratory Data Analysis is the most important and crucial step in Data Science. It not only provides us with information regarding the data points and features but also helps in finding out different data patterns, associations, dependency of the data, etc.

It is one of the time taking processes because we need to analyze data using different statistical methods and visualizations. …


Using Cleantext for cleaning text dataset

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If you’ve ever worked on textual datasets, you must be aware of the garbage that comes with text data. In order to clean this data, we perform certain preprocessing which helps in cleaning and manipulating the data. Preprocessing is an important step because it helps in passing the correct data to the model so that the model can work according to the requirements.

There are certain python libraries that are helpful in performing the preprocessing of the text dataset. One such library is Cleantext, which is an open-source python module i.e, …


Using JoyPy for creating series of Stacked Histograms as Joy Plots

Source: https://scrapbox.io/pycoaj/JoyPy

Visualization is a core part of finding insights and can be used for storytelling. While creating visualization we need to think about which plot to use, which features to consider, what story will be coming out, or finding root cause analysis. Have you ever been stuck with these problems?

There are different python libraries that can be used for data visualization. In this article, will be discussing a rare type of plot known as Joy Plots. …


Using FiftyOne for creating dashboards that helps in building high-quality data and computer vision models

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Visualizing image datasets was never that easy until we got introduced to FiftyOne. It is the perfect tool that not only helps in visualizing the dataset but also helps in understanding different aspects of the dataset, interpreting models, evaluating model prediction, etc. It has a large variety of features and highly recommended for evaluating object detection models, object classification models, finding image uniqueness, etc.

FiftyOne can integrate with multiple tools like PyTorch, Tensorflow, Google AI, Jupyter, Colab, etc. and its core capabilities include curating datasets, evaluating models, finding the annotation mistakes, and many more. …


Using AnimatPlot for Animating Graphs & Plots

Source: By Author

Data Visualization helps in understanding different patterns, associations, visual insights from the data, etc. It is important because it uncovers the mystery behind the data tables in form of charts, graphs, and plots. There is N number of python libraries that help in visualizing the data like Matplotlib, Seaborn, etc.

What if I tell you that you can animate your visualizations? Pretty interesting right! How cool it will be if you can do that. Let’s unravel the mystery behind this and learn about how we can animate our regular plots.

AnimatPlot is an open-source python library that is built on…

Himanshu Sharma

I write about my learnings in the field of Data Science, Visualization, Artificial Intelligence, etc.| Linkedin: https://www.linkedin.com/in/himanshusharmads/

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