Exploring Lux-python package for Visualization

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Photo by Clay Banks on Unsplash

This article is the third part of the series in which we are discussing Automating Exploratory Data Analysis. The link for the first and second parts is given below.

In this article, we will be discussing Lux which is an open-source python package/module used to automate the process of Exploratory Data Analysis using Visualizations.

Lux is a recommendation-based system EDA to help us quickly get around our data. The package helps us by giving us all the possible data combinations and exploring the data based on our own intention.

Lux help us explore data more…


Using Hyperas for Hyperparameter Tuning of Keras Model

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Photo by Uriel SC on Unsplash

Building a model is of no use if you cannot optimize it for a good performance and a higher accuracy. Generally, the model building requires less time than optimizing that model, because during optimization or tuning the model you need to look out for the best parameters which is a time-consuming process.

We can automate this process of finding out the best values for the hyperparameters and getting the highest accuracy of the Keras model. In this article, we will be discussing Hyperas which is an open-source python package used for automating the process of Keras Model Hyperparameter Tuning.

Let’s…


Using Deep Replay for Visualizing the Neural Network Learning

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Keras Model Learning (Source: By Author)

Deep Learning is generally considered a black box technique because you generally can’t analyze how it is working in the back-end. You create a deep neural network, compile it, and then fit it on your data, we know that it will work using neurons transferring the information using different layers and all the activations and other important hyperparameters. But we can’t visualize how information is being transferred or how the model is learning.

What if I tell you that there is a python package that creates the visualizations of how the model is working or learning at each iteration/epoch. You…


Using TPOT to automate machine learning.

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Photo by Markus Spiske on Unsplash

If you have tried making machine learning models then you must have known that it is a time taking process in which you will create different models and find the best model out of them, further you need to tune these models in order to get higher accuracy.

What if I tell you that you can find out the best machine learning model for your data in just a few minutes and that too without even writing a lot of code. …


Tuning Model using HPSklearn

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Photo by Hunter Harritt on Unsplash

Creating a Machine Learning model alone does not solve a problem unless you can optimize it for higher accuracy and better performance. It takes a lot of time to use GridsearchCV and RandomsearchCV to find out the best performing hyperparameters and using these techniques for different models is also a time-consuming process.

HPSklearn is an open-source python library that not only selects the best model for your data but also finds out the best parameters for that model. It is easy to use and contains a large variety of functionalities.

In this article, we will discuss…


Exploring Lens and its Features for EDA

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Photo by Boitumelo Phetla on Unsplash

This article is the fourth part of the series in which we are discussing Automating Exploratory Data Analysis. The link for the previous parts is given below.

In this article, we will be discussing Lens which is an open-source python package/module used to automate the process of Exploratory Data Analysis.

Lens is a library for exploring data in Pandas DataFrames. It computes single-column summary statistics and estimates the correlation between columns.

Let’s start exploring Lens.

Installing LENS

Like any other python package, we can install Lens using pip installation. …


Polyglot- Python package for NLP operations

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Photo by Micah Boswell on Unsplash

Natural Language Processing aims at manipulating the human/natural language to make it understandable for the machine. It deals with text analysis, text mining, sentiment analysis, polarity analysis, etc. There are different python packages that make NLP operations easy and effortless.

All NLP packages have different functionalities and operations which makes it easier for end-user to perform text analysis and all sorts of NLP operations. In this series of articles, we will explore different NLP packages for python and all of their functionalities.

In this article, we will be discussing Polyglot which is an open-source python package used for manipulating text…


Exploring Autoviz and its Features for EDA

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Photo by William Iven on Unsplash

This article is the second part of the series in which we are discussing Automating Exploratory Data Analysis. The link for the first part is given below.

In this article, we will be discussing Autoviz which is an open-source python package/module used to automate the process of Exploratory Data Analysis.

AutoViz performs automatic visualization of any dataset with just one line of code. AutoViz can find the most important features and plot impactful visualizations only using those automatically selected features. Also, AutoViz is incredibly fast so it creates visualization within seconds.

Let’s start exploring AutoViz.

Install AutoViz

We will start by installing…


Using TA-Lib for stock data analysis

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Photo by Markus Spiske on Unsplash

This article is the second part of the series. In order to get started with it please go through the first part which includes the basic installations and initial parameter findings. The link for the first part is given below:

In the previous article, we started with installing the required library that is Ta-Lib and YFinance. We found out five parameters that are used for stock data analysis and in this part we will explore some more parameters which are helpful in predicting the direction and momentum of the stocks.

Let’s get started. In…


Exploring Sweetviz and its Features for EDA

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Photo by Scott Graham on Unsplash

In this series of articles, we will explore python packages/modules which helps in automating the Exploratory Data Analysis part or make it an easy task. For those of you who don’t know what is EDA, it is the process where we tend to analyze the dataset and summarize the main characteristics of the dataset often using visual methods.

Generally, EDA takes a lot of time because we need to analyze and visualize different plots and graphs in order to summarize what type of data we are dealing with, but there are some really…

Himanshu Sharma

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

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