Machine learning engineer

# Time and Space Complexity of Machine Learning Models

• 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…

# 16 Interview Questions That Test Your Machine Learning Skills (Part-2)

## 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% …

# 16 Interview Questions That Test Your Machine Learning Skills (Part-1)

## 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. …

# 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.

# Introduction:

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. …

# Hypothesis test with an example

Untangle hypothesis testing with a detailed walkthrough

# Introduction:

## 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…

# Introduction:

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…

# 16 Interview QuestionsEvery Machine Learning Enthusiast Should Know

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

# Summary of Text To Text Transfer Transformer — T5

## 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…

# LSTM Trainable Parameters

## why 4(nm+n^2+n)?

Lstm cell Architecture 