Pandas reset index – How to reset the index and convert the index to a column?

#pandas reset_index #reset index pandas.reset_index in pandas is used to reset index of the dataframe object to default indexing (0 to number of rows minus 1) or to reset multi level index. By doing so, the original index gets converted to a column. This blog has been contributed by Kaustubh Gupta, under the guidance of …

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How to create a Pandas Dataframe in Python

In Pandas, DataFrame is the primary data structures to hold tabular data. You can create it using the DataFrame constructor pandas.DataFrame()or by importing data directly from various data sources. Tabular datasets which are located in large external databases or are present in files of different formats such as .csv files or excel files can be …

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Pandas Series

#pandas series # pandas create series A pandas Series is a one-dimensional labelled data structure which can hold data such as strings, integers and even other Python objects. It is built on top of numpy array and is the primary data structure to hold one-dimensional data in pandas.

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Matplotlib Tutorial – Principles of creating any plot with the Matplotlib library

Matplotlib is the most popular Python library to plot beautiful graphs. This tutorial guides you to grasp fundamental plotting through reproducible examples. Useful Posts: 1. Matplotlib Beginners Tutorial 2. Top 50 Matplotlib Plots for Data Analysis Overview This tutorial takes you through the following well-rounded concepts: 1. Plotting your first graph 2. Line style and …

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linear regression with tensorflow

How to implement Linear Regression in TensorFlow

Linear Regression is one of the fundamental machine learning algorithms used to predict a continuous variable using one or more explanatory variables (features). In this tutorial, you will learn how to implement a simple linear regression in Tensorflow 2.0 using the Gradient Tape API. Overview In this tutorial, you will understand: Fundamentals of Linear Regression …

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Brier Score – How to measure accuracy of probablistic predictions

Brier score is an evaluation metric that is used to check the goodness of a predicted probability score. This is very similar to the mean squared error, but only applied for prediction probability scores, whose values range between 0 and 1. Overview In this tutorial, you will understand: What is Brier score? How is Brier …

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Julia Programming Language for Pythonistas – A Practical Tutorial

Julia programming language tutorial is an introduction to Julia for Python programmers. It will go through the most important Python features (such as functions, basic types, list comprehensions, exceptions, generators, modules, packages, and so on) and show you how to code them in Julia IDE. By the end of this Julia tutorial, you will have …

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dask parallel computing in python

Dask – How to handle large dataframes in python using parallel computing

Dask provides efficient parallelization for data analytics in python. Dask Dataframes allows you to work with large datasets for both data manipulation and building ML models with only minimal code changes. It is open source and works well with python libraries like NumPy, scikit-learn, etc. Let’s understand how to use Dask with hands-on examples. Dask …

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Text Summarization Approaches

Text Summarization Approaches for NLP – Practical Guide with Generative Examples

Text summarization in NLP is the process of summarizing the information in large texts for quicker consumption. In this article, I will walk you through the traditional extractive as well as the advanced generative methods to implement Text Summarization in Python. Contents 1. Introduction 2. Types of Text Summarization 3. Text Summarization using Gensim 4. …

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Bias Variance Tradeoff – Clearly Explained

Bias Variance Tradeoff is a design consideration when training the machine learning model. Certain algorithms inherently have a high bias and low variance and vice-versa. In this one, the concept of bias-variance tradeoff is clearly explained so you make an informed decision when training your ML models Bias Variance Tradeoff – Clearly Explained. Photo by …

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Gradient Boosting – A Concise Introduction from Scratch

Gradient Boosting is a machine learning algorithm, used for both classification and regression problems. It works on the principle that many weak learners (eg: shallow trees) can together make a more accurate predictor. A Concise Introduction to Gradient Boosting. Photo by Zibik How does Gradient Boosting Works? Gradient boosting works by building simpler (weak) prediction …

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Complete Guide to Natural Language Processing (NLP) – with Practical Examples

Natural language processing (NLP) is the technique by which computers understand the human language. NLP allows you to perform a wide range of tasks such as classification, summarization, text-generation, translation and more. NLP has advanced so much in recent times that AI can write its own movie scripts, create poetry, summarize text and answer questions …

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Portfolio Optimization with Python using Efficient Frontier with Practical Examples

Portfolio optimization in finance is the technique of creating a portfolio of assets, for which your investment has the maximum return and minimum risk. Investor’s Portfolio Optimization using Python with Practical Examples. Photo by Markus In this tutorial you will learn: What is portfolio optimization? What does a portfolio mean? What are assets, returns and …

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Machine Learning A-Z™: Hands-On Python & R In Data Science

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Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science