November 28, 2022 Esha Narang
Reading Time: 2 minutes

AI ML Keywords –

Machine Learning:

  • Machine learning, a subset of artificial intelligence, allows systems to discover patterns in data and then get easier with experience.

Artificial Intelligence:

  • A machine’s ability to replicate as humans do, such as perceiving, learning, reasoning, and solving problems.


  • A data set is a group of data, these data can be in numerical data, categorical data, correlated data.


  • The use of labelled datasets defines the machine learning strategy known as supervised learning. Labeled inputs and outputs allow the model to analyze its precision and improve over time.


  • Unsupervised learning analyses and groups unlabeled data sets using machine learning methods. For anomaly detection, recommendation engines, customer personas, and medical imaging, unsupervised learning is a wonderful fit.

Linear Regression:

  • A variable’s value can be predicted using linear regression analysis depending on the value of another variable. Supervised machine learning techniques include linear regression.

Logistic Regression:

  • A statistical analysis technique called logistic regression uses the data from a data set to predict a binary outcome, such as yes or no. One illustration of supervised learning is logistic regression.

Data Collection:

  • Data collection is the process of gathering data from various offline and online sources by scraping, collecting, and loading it.

Data Preparation:

  • Data preparation is also known as data “pre-processing. For the purposes of machine learning projects, data preparation is the process of obtaining, combining, cleaning, and processing raw data.


  • Accuracy, precision, and recall are the three primary measures used to evaluate the efficiency of a classification algorithm.


  • When predicting the likelihood of a specific outcome, “prediction” refers to the result of an algorithm that has been trained on past data and applied to current data.


  • A pattern is a series of data that takes on a recognized form, which analysts then look for in the present data.

Natural Language Processing:

  • natural language processing is a form of Ai technology (AI), enables machines to recognize and interpret human language in addition to reading it.


  • Before beginning to use machine learning, one must first perform data analysis, which involves obtaining, cleaning, exploring, and visualizing data.


  • A robot is a type of automated machine that can carry out particular activities quickly and accurately.


  • the process of getting data ready for analysis by getting rid of or changing data that is missing, inaccurate, redundant, or formatted incorrectly.


  • Simply said, training a model involves learning (trying to decide) appropriate values for each weight and bias from labelled samples.


  • the procedure by which a fully trained model’s performance is evaluated on a test dataset.
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