Machine Learning

machine learning interview questions and answers

19 Basic Machine Learning Interview Questions and Answers

There are several companies who hire data engineers or data scientists to make their data more reliable and secure; and for that purpose they use machine learning. The companies may hire number of engineers who are data analyst, machine learning engineers, deep learning engineer. All these posts are of similar job nature. The employer can …

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Linear Algebra in TensorFlow

Linear Algebra in TensorFlow (Scalars, Vectors & Matrices)

Linear Algebra in TensorFlow: TensorFlow is open source software under Apache Open Source license for dataflow which is frequently being used for machine learning applications like deep-neural-network to improve the performance of search engines, such as, Google, image captioning, recommendation and translation. For example, when a user types a keyword in Google’s search bar, it …

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types of machine learning

4 Types of Machine Learning (Supervised, Unsupervised, Semi-supervised & Reinforcement)

Machine learning is a subfield of Artificial Intelligence. The concept of machine learning originally started in 1959 by an American Arthur Samuel. He was an expert in the field of computer gaming and intelligent machines. In this post, we are going to discuss the types of machine learning. There are four major types of machine …

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7 commonly used machine learning algorithms for classification

7 Commonly Used Machine Learning Algorithms for Classification

Generally, data is a set of factual information based on numbers, words, observations, measurements that can be used for calculation, discussion and reasoning. The rough dataset is the essential foundation of data science and it may be of diverse types, such as structured data and unstructured data and semi-structured. Structured data is formatted in tabular …

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Support Vector Machine (SVM) in Python

Implementing Support Vector Machine (SVM) in Python

Machine Learning is the most famous procedure of foreseeing the future or arranging data to help individuals in settling on essential choices. The algorithms are trained over models through which they gain information from past encounters so as to make forecasts about what’s to come. There are three types of Machine learning i.e. supervised learning, …

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Machine-Learning-With-Python-A-Real-Life-Example

Machine Learning With Python – A Real Life Example

In this article we are going to discuss machine learning with python with the help of a real-life example. Before we proceed towards a real-life example, just recap the basic concept of Linear Regression. Usually, Linear Regression is used for predictive analysis. It is a linear approximation of a fundamental relationship between two (one dependent …

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K Means Clustering Example in Python

What is Clustering & its Types? K-Means Clustering Example (Python)

Cluster Analysis Cluster is a group of data objects that are similar to one another within the same cluster, whereas, dissimilar to the objects in the other clusters. Cluster analysis is a technique used to classify the data objects into relative groups called clusters. Clustering is an unsupervised learning approach in which there are no …

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logistic regression python example

Logistic Regression (Python) Explained using Practical Example

Logistic Regression is a predictive analysis which is used to explain the data and relationship between one dependent binary variable and one or more nominal, ordinal, interval or ratio-level independent variables. It is mostly used in biological sciences and social science applications. For instance, predict whether received email is spam or not. Similarly, predict whether …

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imple & Multiple Linear Regression [Formula and Examples]

Simple and Multiple Linear Regression in Python

Generally, Linear Regression is used for predictive analysis. It is a linear approximation of a fundamental relationship between two or more variables. Main processes of linear regression Get sample data Design a model that works best for that sample Make prediction for the whole population Main uses of regression analysis Finding the strength of predictors …

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