Learn From Data

https://www.analyticsvidhya.com/blog/2021/07/the-measure-of-central-tendencies-in-statistics-a-beginners-guide/

The Measure of Central Tendencies in Statistics -A Beginner's Guide This article was published as a part of the Data Science Blogathon Statistics. Whenever I hear this term, I imagine of below Image is taken from www. mathnstuff.com Looks pretty scary to me. In this blog, my aim is to introduce you to the measure of central tendency used in statistics in the

https://towardsdatascience.com/accuracy-recall-precision-f-score-specificity-which-to-optimize-on-867d3f11124

Accuracy, Recall, Precision, F-Score & Specificity, which to optimize on? Based on your project, which performance metric to improve on?

https://medium.com/coders-camp/130-python-projects-with-source-code-61f498591bb

130+ Python Projects with Source Code 130+ Python Projects with source code: Solved and Explained

https://medium.com/pythoneers/30-basic-machine-learning-questions-answered-692acd10841f

30 Basic Machine Learning Questions Answered To Check and Increase Your Knowledge of ML 🤔

https://www.analyticsvidhya.com/blog/2021/06/random-forest-for-time-series-forecasting/

Random Forest for Time Series Forecasting This article was published as a part of the Data Science Blogathon Introduction Random Forest is a popular machine learning algorithm that belongs to the supervised learning technique. It is an ensemble learning method, constructing a multitude of decision trees at training time and outputting the c...

https://www.freecodecamp.org/news/what-is-mlops-machine-learning-operations-explained/

What is MLOps? Machine Learning Operations Explained In this article, I'll teach you about Machine Learning Operations, which is like DevOps for Machine Learning. Until recently, all of us were learning about the standard software development lifecycle (SDLC). It goes from requirement elicitation to designing to development to testing to deployment, a...

https://towardsdatascience.com/top-10-github-repos-to-bookmark-right-now-b0bc62436ffcvv

Medium

https://rubikscode.net/2020/11/15/top-9-feature-engineering-techniques/

Top 9 Feature Engineering Techniques with Python In this article, we explore several optimization techniques and implement them in Python from scratch.

Log Transform:-

Logarithm transformation (or log transform) is one of the most commonly used mathematical transformations in feature engineering. What are the benefits of log transform:

->It helps to handle skewed data and after transformation, the distribution becomes more approximate to normal.

->In most of the cases the magnitude order of the data changes within the range of the data. For instance, the difference between ages 15 and 20 is not equal to the ages 65 and 70. In terms of years, yes, they are identical, but for all other aspects, 5 years of difference in young ages mean a higher magnitude difference. This type of data comes from a multiplicative process and log transform normalizes the magnitude differences like that.

->It also decreases the effect of the outliers, due to the normalization of magnitude differences and the model become more robust.

*A critical note: The data you apply log transform must have only positive values, otherwise you receive an error. Also, you can add 1 to your data before transform it. Thus, you ensure the output of the transformation to be positive.

https://levelup.gitconnected.com/21-python-mini-projects-with-codes-c4126e4131e4

21 Python Mini Projects With Code The Best way to learn a programming language is to build projects in it

https://www.analyticsvidhya.com/blog/2016/02/time-series-forecasting-codes-python/? #

A comprehensive beginner's guide to create a Time Series Forecast (with Codes in Python and R) Overview Learn the steps to create a Time Series forecast Additional focus on Dickey-Fuller test & ARIMA (Autoregressive, moving average) models Learn the concepts theoretically as well as with their implementation in python   Introduction Time Series (referred as TS from now) is considered to be o...

Difference Between OLTP and OLAP