Probability and Statistics play a very important role in the field of data science and machine learning. In this blog post you will learn the concept of proportional sampling and how can we implement it from scratch without using any library Proportional Sampling Let us take an example of tossing a die to better understand …
Hey Finxters! I have another top 10 cheat sheets for you to consider and tape to your wall. In this article, I will be presenting the best Pytorch cheat sheets available. Keep them handy when you are working on a project and would like to spend less time searching for the correct function you are …
Have a little time to learn Tensorflow 2.0 with your Machine Learning? In this article, I have put together the 10 best Tensorflow cheat sheets for you to hang on the wall above your desk. Whenever you need a reference, keep these handy cheat sheets available!! Cheat Sheet 1: BecomingHuman.AI becominghuman.ai has multiple cheat sheets …
Introduction Regression is a supervised learning technique that defines the relationship between a dependent variable and the independent variable(s). Regression models describe the relationship between the dependent and independent variables using a fitting line. In the case of linear regression models, this is a straight line while in the case of logistic and nonlinear regression models a …
Do you need a little help learning Scikit-Learn in Python? Or maybe you just finding it hard to remember all the different commands to perform different operations? All of those formulas can be confusing and hard to remember. Have no fear!! I have put together 10 of the Best Python Scikit-Learn cheat sheets for you …
[Collection] 10 Scikit-Learn Cheat Sheets Every Machine Learning Engineer Must Have Read More »
If you are a data scientist or aspire to be one investing your time in learning natural language processing (NLP) will be an investment in your future. 2020 saw a surge in the field of natural language processing. In this blog post you will discover 5 popular NLP libraries, and it’s applications. Preprocessing Libraries Preprocessing …
The following is a conversation with an AI assistant. The assistant is helpful, creative, clever, and very friendly. Human: Hello, who are you? AI: I am an AI created by OpenAI. How can I help you today? Human: My name is Chris, and I’d love to teach people to code. AI: I would recommend the …
A Chat Conversation with OpenAI About Teaching, Programming, and Life Read More »
Machine learning is one of the fastest-growing technologies and it is going to play a pivotal role in the future of technology. With the help of various algorithms machine learning is used to build mathematical models that have the capability to make predictions based on historical data or past data. Currently, it is already being …
Introduction To Machine Learning And Its Applications Read More »
Introduction Data preprocessing is a technique that is used to transform raw data into an understandable format. Raw data often contains numerous errors (lacking attribute values or certain attributes or only containing aggregate data) and lacks consistency (containing discrepancies in the code) and completeness. This is where data preprocessing comes into the picture and provides a proven method of …
The Pandas map( ) function is used to map each value from a Series object to another value using a dictionary/function/Series. It is a convenience function to map values of a Series from one domain to another domain. Pandas map function Let’s have a look at the documentation of the map function, map is a …
This article explores the use of the functions .UnivariateSpline() and .LSQUnivariateSpline(), from the Scipy package. What Are Splines? Splines are mathematical functions that describe an ensemble of polynomials which are interconnected with each other in specific points called the knots of the spline. They’re used to interpolate a set of data points with a function …
Fitting Data With Scipy’s UnivariateSpline() and LSQUnivariateSpline() Read More »
