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This article aims to build conventional machine learning models in python languages, such as Random Forest and Linear Regression, to predict Bioactivity values of a molecule from the ChEMBL dataset.

What you will learn

  • How to Use ChEMBL Python API for Data collection
  • Practical Application of Lipinski's descriptors, PaDEL.
  • Using rdkit python library

Installing the required libraries

pip install pandas
pip install np
pip install matplotlib
pip install sklearn
pip install chembl_webresource_client
pip install seaborn
##Now in order to install rkdit use
conda install -c conda-forge rdkit

In case you face any error, please visit this link.

Also, note that you must have python version 2.7 - 3.6…

In this article, I will show you how you can write a python code for planing the path of a robot using potential fields of obstacle and the goal.


The autonomous navigation of a robot relies on the robot's ability to achieve its goal, avoiding obstacles in the environment. In some cases, the robot has complete knowledge of its environment and plans its movement based on it. In general, the robot only has an idea about the goal and should reach it using its sensors to gather information about the environment.

Local path planning should be performed in real-time, and…

This article will help you write the python code to extract the reflectance from DN(Digital Number) of the Satellite images. For this tutorial, we will use images Landsat of 7 and Landsat 8 both. You can get the whole code here.

Why can’t you use the Satellite images Directly?

Atmospheric influence on the spectral response pattern

Irradiance originates from two sources :

  1. Directly reflected sunlight
  2. Diffused Skylight
  • The relative dominance of sunlight versus skylight in any given image
    is strongly dependent on weather conditions (e.g., sunny vs. hazy vs.
  • Irradiance varies with the seasonal changes in solar elevation angle and
    the changing distance between the earth and sun.


I am an experienced Android developer and ML enthusiasts

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