What do you mean by Ensemble techniques? First lets understand what is Ensemble.

Ensemble : — A group producing a single effect. Ensemble methods are techniques that create multiple models and then combine them to produce improved results.

Ensemble methods can be divided into two groups:

Sequential ensemble methods where the base learners are generated sequentially (e.g. AdaBoost).

Parallel ensemble methods where the base learners are generated in parallel (e.g. Random Forest).

Ensemble methods are meta-algorithms that combine several machine learning techniques into one predictive model in order to Decrease variance, Decrease bias and Improve predictions.

Decrease variance == Bagging
Decrease bias == Boosting
Improve predictions == Stacking


There are many ways to share a Jupyter notebook with others (e.g., Github). However, the recipient can only interact with notebook file if they already have the Jupyter Notebook environment installed.

But what if you want to share a fully interactive Jupyter notebook that doesn’t require any installation? Or, You don’t need to buy a GPU for machine learning work? Or, you want to create your own Jupyter notebooks without installing anything on your local machine?


In the field of Data Science, there is nothing more important than understanding the data. Understanding the data can save our time and make our model more strong. There are a lots of different tools and techniques which can be used to conduct analysis.

We generally come across Univariate, Bivariate and Multivariate analysis terms while giving interviews or applying stats on our data. For every Data job understanding of these concepts are must.

Univariate analyses are descriptive statistical analysis techniques. Univariate analysis is the simplest form of analyzing data. …


Number system is basically the classification of all the possible numbers. A number system is used to represent numeric values. Every number system consist of some symbols which can be used to represent various numbers.

Binary number system (Base — 2) — 0,1
Octal number system (Base — 8) — 0,1,2,3,4,5,6,7
Decimal number system (Base — 10) — 0,1,2,3,4,5,6,7,8,9
Hexadecimal (Base — 16) — 0,1,2,3,4,5,6,7,8,9,a,b,c,d,e,f

Binary (bin) : — We can convert any number to Binary values. i.e., — 0 and 1. E.g., Binary value for 25 is “11001”. In python, it can be seen as “0b11001”. 0b represent type…

Working as a Data Scientist in UHG. Having experience in Machine Learning, Deep learning and Natural Language Processing (NLP).

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