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Machine learning engineer
Source: ActiveLamp
  • The train time complexity of machine learning model — The amount of time taken to train the model
  • The test time complexity of the machine learning model — Time took to predict output for a given input query point.

Time complexity is an essential aspect to know when anyone wants…

Image by mohamed Hassan from Pixabay

1. Explain the 68–95–99 rule in normal distribution?

  • As shown in the image below. nearly 68% of the data is within 1 standard deviation (σ) from the mean (μ), nearly 95% of the data is within 2 standard deviations (σ) from the mean (μ), and nearly 99.7% …

1) What is the internal covariate shift and what are the consequences of it?

  • Internal covariate shift occurs when the statistical distribution of input data changes drastically with respect to other input data.
  • When the input data distribution changes, hidden layers try to learn to adapt to the new distribution. …

Machine learning is not model training.

Photo by Tolga Ulkan on Unsplash

1) Contents

a. Data Collection

b. Exploratory Data Analysis

c. Data Preprocessing

d. feature engineering

e. Feature Selection

f. Model Selection and Hyperparameter Tuning

h. Model Evaluation and Analysis

2) Data Collection :

  • Many people think machine learning only concerns train models, but in fact, there are many to follow before training our model.


It's very important to know where our model works well and where it fails. If there is a low latency requirement, definitely KNN will be a worse choice. …

Untangle hypothesis testing with a detailed walkthrough


what is a Hypothesis testing?

  • A statistical test that gives evidence to accept or reject the null hypothesis with a sample of data from the condition which is true for the entire population.
  • If we have to show two distributions are different then we prove by contradiction by…


This blog strictly limits to code walkthrough to generate a summary using Text to text transfer transformer(T-5). If you guys are curious about how T-5 works and how it was pretrained and fine-tuned on downstream NLP tasks check out the following the blog.

1) Installing Hugging-face transformers:

  • Hugging face an open-source NLP library that…

A Machine Learning Engineer has to cover the breadth concepts in ML, DL , Probability , Stats, and coding with a good depth of understanding . …

A brief overview of Google T5 transformer

The basic approach behind Text to text transfer transformer is to take every NLP problem as the TEXT — TEXT approach similar to the Sequence -sequence model.

Text-Text framework:

T5 uses the same model for all various tasks by the way we tell the model which task to perform by…

Gundluru Chadrasekhar

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