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Last updated: Dec 10, 2021

KickStart to Machine Learning

Gear to know about libraries and packages that are essential to perform Machine learning techniques and build models. Master code implementation of Numpy and Pandas with Linear Algebra including matrices, vectors, and statistics.
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Numpy and Linear Algebra

Learn about the Numpy functions needed to get started with Machine Learning, as well as code snippets and mathematical concepts related to Linear Algebra.
NumPy Basics
In this blog post, we’ll learn the basics of the NumPy library. From the installation to performing basic operations on arrays, we’ll cover all aspects of the NumPy package.
How to install numpy in python EASY
NumPy is an open-source library for the Python programming language. This blog will discuss how to install NumPy in Python along with its features.
Random Generators in Numpy
In this blog, we’ll learn about different random functions in NumPy.
Numeric Datatypes in NumPy EASY
NumPy is a Python library that amplifies arrays' abilities by allowing mathematical operations. This article focuses on the Numeric Datatypes in NumPy.
Statistical Computing using NumPy
In this blog, we’ll learn about different statistical functions in NumPy.
numpy.convolve() Method in Python EASY
In this article, we will discuss the NumPy library in Python and its important function, numpy.convolve() Method in Python
Basics of Matrix, Vector, and various matrix operations
This blog will study basic linear algebra, including Matrix, Vector, and various matrix operations.
Difference Between Flatten and Ravel Functions in Numpy EASY
In this article, we will discuss Flatten Function, Ravel Functions, their Syntax and the difference between them.
Linear Equations, Vector Norms, and Covariance matrix
In this blog, we’ll learn about some essential mathematical concepts used in machine learning.
Important Numpy Functions for ML
In this blog post, we'll be learning about popular Numpy functions in the field of Machine Learning. We would also be testing the same and observing the results.
String Information in NumPy MEDIUM
In this article, we will discuss String operations, and their various advantages and disadvantages.
Manipulating Data Types in NumPy EASY
In the article “Manipulating Data Types in NumPy”, we will discuss the Numpy Arrays and manipulate the data types using the astype() function.
Numpy.Transpose() in Python EASY
In this article, we will discuss the NumPy transpose in python. We will be learning about the manual method also to calculate the transpose.
NumPy.Reshape() in Python EASY
This article will discuss NumPy reshape in Python. We will discuss its syntax, parameters and other special cases of NumPy reshape function.
Numpy polyfit() Method in NumPy EASY
In the article “Numpy polyfit() Method in NumPy”, we will discuss the Numpy Library, the Polyfit() method, and the implementation of the Polyfit() method.
Convert Python Data Structures to Numpy Array EASY
In this blog, we will see various conversions of Python data structures to Numpy arrays using the np.array() method in Numpy.
numpy.log() in Python EASY
This article will teach us about numpy.log() in Python, key features of Numpy and use of this logarithmic function.
numpy.fft() EASY
In this article, we will discuss NumPy, its syntax and the available functions of numpy.fft()
Byte Swapping in NumPy EASY
In this article, we will discuss the need for byte swapping, how byte swapping can be done, and lastly, and implementation of byte swapping.
Vectorization in NumPy MEDIUM
This article will teach us about Vectorization in Numpy, Numpy arrays, vectorized options and the use cases of vectorization, etc.
numpy.arctan2() in Python EASY
This article will teach us about numpy.arctan2() in Python, its syntax and parameters, working, real-world use cases along with examples.
stack() Function in NumPy MEDIUM
In this article, we will discuss the stack() function, its use in 1-D, 2-D and 3-D arrays and its various functions.
Difference Between np.mean() Vs np.average() MEDIUM
In this article, we will discuss np.mean(), np.average(), their Syntax and the difference between them.

Pandas and Datasets

Pandas is a very important and interesting Python library for data handling and dataset operations. Learn about its methods, applications, and implementations that will help you clean up your data
Getting started with Pandas
In this article, we will see the installation, how to use it while making machine learning, deep learning models, and other basic functionalities of pandas.
Pandas Read Excel EASY
In this article, you’ll learn what pandas read excel is, the different parameters of pandas read excel, and some examples of pandas read excel.
Parallelizing Your Pandas Workflow EASY
This article will cover the concept of parallelization and how to apply it to Pandas and also discuss various ways to implement parallelization.
How to Install Pandas in Python EASY
In this article, we will learn how to install Pandas in Python with proper steps and what pandas is all about.
Import Pandas as pd EASY
Pandas is open-source software written library in Python used for data manipulation and analysis.
Must Know Functions in pandas
In this blog, we will learn about the Pandas library and some must-know functions in Pandas. We'll go through some simple examples to better understand all the functions.
I/O with Pandas EASY
In this blog, we will discuss Pandas and I/O with Pandas. We will also see how to install and import pandas as well.
Pandas Profiling in Python EASY
In this blog, we will discuss about Pandas profiling in Python. We will discuss about how to use Pandas profiling by taking an example.
pandas.at() Method EASY
This article will cover Pandas at() with its syntax, errors and return value and discuss several working examples.
Selecting, Extracting and Slicing Dataframes Pandas
This article teaches you about selecting, extracting, and slicing dataframes in Pandas.
Python DataFrame EASY
This blog covers the concept of DataFrame in Python with examples and various methods in DataFrame.
Labels in Pandas Series MEDIUM
In this blog, we will discuss Labels in Pandas Series, Several motives of Labels in the Pandas Series, and some frequently asked questions.
Pandas query() Method EASY
In this article, we will discuss the Pandas query(), its syntax and several working examples with some faqs.
Pandas explode() Function EASY
This article discusses the explode() function provided by the Pandas library with the help of examples.
Imputation in Pandas EASY
In this article, we will discuss the Imputation in Pandas in detail with the help of examples and will check some FAQs.
Author Alisha
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Groupby.count in Pandas
This article discusses the groupby() and count() methods available in the Pandas library.
Pandas rank() Function EASY
This article discusses the rank() function provided by the Pandas library with the help of examples.
Pandas dataframe.shift() EASY
In this blog, we will discuss about Pandas dataframe.shift(). We will discuss its syntax, parameters, and some examples based on it.
Caveats and Gotchas in Pandas EASY
In this blog, we will discuss about caveats and gotchas in Pandas. We will see various ways to deal with caveats and gotchas in Pandas.
Pandas Pivot Table MEDIUM
This article explains how to use pivot_table() in Python. The article covers the basics of creating a pivot table, the data needed, and how to avoid mistakes. It also includes some examples to help readers understand better.
Pandas Melt() Function EASY
In this article, we will discuss the Pandas Melt() Function in detail with the help of examples and will check some FAQs.
Author Alisha
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ewm() Method in Pandas EASY
In this blog, we will discuss about ewm() Method in Pandas. We will discuss its syntax, parameters, and some examples based on it.
Time Series and Timedelta in Pandas EASY
This article will cover Time Series with basic operations and Timedelta in Pandas and will understand them by discussing several working examples.
Panel in Pandas EASY
This article will cover the Panel in Pandas and how to create it and will cover basic operations with the help of examples.
Resampling, Rolling Calculations, and Differencing in Pandas EASY
This article will cover three important techniques for time series analysis, which are resampling, rolling calculations, and differencing in Pandas, with examples.
Difference Between loc() and iloc() in Pandas EASY
loc() is for selecting data by label e.g., column or row names, while iloc() is for selecting data by integer position e.g., row and column indices.
Pandas Index and Pandas Reindex EASY
In this article, we will discuss the Pandas Index and Pandas Reindex in detail with the help of examples and will check some FAQs.
Concatenate and Reshape Data frames in Pandas EASY
This article teaches you how to concatenate and reshape data frames in Pandas.
Advanced functions in Pandas
In this article, we will learn the important function that every Machine Learner must know while using pandas.
How To Rename Columns In Pandas (With Examples) MEDIUM
In this article, we will discuss what the Pandas DataFrame is and the various methods through which we can Rename Columns in Pandas.
Introduction to Reset Index in Pandas Dataframe EASY
This blog will help you to clear your understanding of how to reset index in pandas dataframe and dry run with various examples to have a clear idea.
Pandas MultiIndex MEDIUM
In this article, we will discuss the Pandas Multi Index in detail with the help of examples and will check some FAQs.
Author Alisha
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Python String join() Method EASY
In this blog, we’ll study the concept of Join in Python. We will further discuss how to implement joins using Pandas in Python.

scikit-learn Library

The scikit-learn package is a fascinating and valuable library for machine learning operations. It includes a wide range of supervised and unsupervised learning algorithms, from classification to regression. Methods and functions that are simple to invoke.
Basic Guide to Scikit-learn
In this blog, we will learn a critical module or library for machine learning: Scikit-learn and its use cases and the implementation with the help of an example.
Must Know Functions in Scikit-Learn
In this blog post, we'll learn about some essential scikit-learn functions. We will be testing the same and observing the results.
Preprocessing with scikit-learn MEDIUM
In this article, you'll learn how to do the Preprocessing with scikit-learn
Implementing Linear Models Using scikit-learn MEDIUM
In this article, we will explain the implementation of linear models using scikit-learn
Ensemble Method using scikit-learn MEDIUM
In this article, we will cover the topic of the ensemble method in machine learning.
MultiClass and Multioutput Classification using scikit-learn MEDIUM
In this article, we will cover the topic of multiclass, multilabel, and multioutput classification and after that, we will also have a look at their implementations using scikit-learn.
Feature Selection in ML with scikit-learn MEDIUM
In this article, we will cover the topic of feature selection in ML with scikit-learn.