Idea Innovators

Idea Innovators we want to try to give a new idea by new invention.

09/10/2025

I got over 30 reactions on one of my posts last week! Thanks everyone for your support! 🎉

Kernel Density Estimation (KDE):Kernel Density Estimation (KDE) is a data visualization technique used to estimate the p...
08/10/2025

Kernel Density Estimation (KDE):
Kernel Density Estimation (KDE) is a data visualization technique used to estimate the probability density function of a continuous variable. It smooths the data using a kernel function (like Gaussian) to show where values are concentrated, making it easier to identify patterns, peaks, and data distribution shapes compared to a histogram. In data science, KDE is often used to understand data distribution and detect outliers or clusters.
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Horizontal bar plot graph :A Horizontal Bar Plot is a type of graph used to display and compare categorical data. In thi...
07/10/2025

Horizontal bar plot graph :
A Horizontal Bar Plot is a type of graph used to display and compare categorical data. In this plot, bars are drawn horizontally instead of vertically, making it easier to read long category names. The length of each bar represents the value or frequency of the category. It’s commonly used in data science to visualize rankings, comparisons, or distributions across categories.
My Portfolio: https://www.behance.net/.../Data-Science-and-Machine...
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Hexagonally Based Histogram:A Hexagonally Based Histogram (Hexbin Plot) is a data visualization used to display the rela...
06/10/2025

Hexagonally Based Histogram:
A Hexagonally Based Histogram (Hexbin Plot) is a data visualization used to display the relationship between two numerical variables. Instead of using square bins like a regular histogram, it divides the plot area into hexagonal cells. Each hexagon’s color or shade represents the number of data points within it. This type of plot is especially useful for visualizing the density of large datasets and helps identify clusters or patterns more clearly than scatter plots.
My Portfolio: https://www.behance.net/.../Data-Science-and-Machine...
Book for free consultancy: https://calendly.com/abdulkayumgpmcbd/30min
Hire me: https://www.fiverr.com/s/Q7VB0oR
WhatsApp: 008801784388214

Area plot graph: An Area Plot is a type of graph used to represent quantitative data visually. It shows how one or more ...
05/10/2025

Area plot graph:
An Area Plot is a type of graph used to represent quantitative data visually. It shows how one or more groups’ numerical values change over time or another continuous variable. Area plots are similar to line charts, but the space between the line and the axis is filled with color or shading, making it easier to compare cumulative trends or proportions. They are useful for showing overall trends and the contribution of each category to the total.
My Portfolio: https://www.behance.net/moodboard/220671463/Data-Science-and-Machine-Learning
Book for free consultancy: https://calendly.com/abdulkayumgpmcbd/30min
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WhatsApp: 008801784388214

A stacked bar plotA stacked bar plot is a type of bar chart used in data science and machine learning to visualize the c...
03/10/2025

A stacked bar plot
A stacked bar plot is a type of bar chart used in data science and machine learning to visualize the composition of different categories within a dataset. In this plot, bars are divided into segments, with each segment representing a sub-category. The length of the entire bar shows the total value, while the stacked segments show how that total is distributed among the sub-categories.

My Portfolio: https://www.behance.net/moodboard/220671463/Data-Science-and-Machine-Learning
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I'm here to help with your Data Science and Machine Learning projects with Python.My Services:Data Analysis and Data Vis...
30/09/2025

I'm here to help with your Data Science and Machine Learning projects with Python.

My Services:
Data Analysis and Data Visualization:
Data cleaning and preprocessing
Creating clear data visualizations like bar charts, pie charts, line graphs, and scatter plots.
Machine Learning Models:
Building models for classification and regression tasks.
Using algorithms like Linear Regression, Logistic Regression, Naive Bayes, Decision Trees, Random Forests, and Deep Learning.
Model Training and Deployment:
Training models to make accurate predictions.
Evaluating model performance.

My Portfolio: https://www.behance.net/moodboard/220671463/Data-Science-and-Machine-Learning
Book for free consultancy: https://calendly.com/abdulkayumgpmcbd/30min
Hire me: https://www.fiverr.com/s/Q7VB0oR
WhatsApp: 008801784388214

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