Data Analyst Enthusiastic

*OpenCV** **also termed as ‘Open Source Computer Vision Library’ is an open-source library that includes several hundreds of computer vision algorithms.*

Real-life problems requires to utilize multiple building blocks together in order to achieve the desired outcome. So, we just have to understand what modules and functions are needed to get what you want!

Today, we will be getting dive into some basic functionalities that can help you to get start with OpenCV :)

OpenCV (Open Source Computer Vision Library) is an open source computer vision and machine learning software library. …

Built on-top of NumPy, SciPy and Matplotlib,the Scikit-learn is the robust library used in machine learning.

- Provides efficient tools for machine learning .
- Provide statistical model including classification, regression, clustering.
- Covers most machine-learning tasks and scales to most data problems.

`pip install -U scikit-learn`

`conda install scikit-learn`

Scikit-learn library focus more on modeling the data rather than loading, manipulating and summarizing data.Some of the popular groups of models provided by Sklearn are :

- Supervised Learning algorithms : Linear Regression, Support Vector Machine (SVM), Decision Tree etc.
- Unsupervised Learning algorithms : clustering, factor analysis,Principal Component Analysis, unsupervised neural networks etc.
- Cross…

As Discussed in Previous Post,Pandasis a software library written for thePythonprogramming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series. Let’s get dive into the Basics of Pandas.If You haven’t Read the Previous post then, click below https://medium.com/@abhishek_iiit/basic-introduction-to-pandas-pandas-series-part-1-ee08073b109

We will be using the Dataframe as shown below, but before that, we try to import *Pandas* and *Numpy* by the command:

*import NumPy as npimport pandas as pd*

Pandasis a software library written for thePythonprogramming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series. Let’s get dive into the Basics of Pandas.

**Case 1: Basic of Pandas Series**

According to *Wikipedia*, NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.

Being the Library of Python, it can perform algorithm Faster than the default Python’s library. Without wasting much time, Lets Dive into the Basics of Numpy that can help in the Data Science field. We will be going through Every Case important in the *Numpy*

**Case 1:Memory Allocation**

**Harvard University** labeled the profession “** the sexiest job of the 21st century.**” And according to

Let’s Know the Basic tools Everyone should know when starting with **Data Analysis with Python**

**Step 1: Getting Started(Data Extraction)**

You can use *Jupyter Notebook* (https://jupyter.org/) directly. It’s a free and open-source web application you can work on.

**1**.Import your Python Library into your Notebook via