machine-learning

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Machine learning in Drug Discovery

In this article, we want to identify the compounds with the best effect on Acetylcholinesterase protein using XGBoost Machine Learning Algorithm. We will be using the famous ‘Chembl’ database to demonstrate the complete use-case.

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Sentiment Analysis using Naive Bayes

Sentiment Analysis is a technique that comes under natural language processing(NLP) and is used to predict the emotions reflected by a word or a group of words. In this blog, we will discuss one of the simplest probabilistic algorithms, Naive Bayes to predict the sentiments using their tweets.

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Python Data Structures for ML and Data Science: Tuples and Lists

In this article, we will discuss two data structures tuples and lists in Python. They are frequently used in Machine Learning and Data Science. These data types are also called compound data types because they can store mixture of primitive data types like Strings, ints, and floats.

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Handling Date & Time in Python

Temporal attributes are crucial since they help clarify the cyclic trends in data. This article will talk about all basic date-time manipulations, explorations, transformations, and some miscellaneous applications.

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Applications of Regex in Data Science

In this blog, we will focus on the industrial applications of regex by implementing it to some tedious tasks that wouldn’t be possible without regular expressions, like Web-Scrapping & Data Collection, text processing and pattern matching.

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Employee Attrition Rate Prediction Using Machine Learning

Here we have demonstrated a deeper data analysis of company's attrition rate and built a logistic regression model to predict it. This project can help management team to control the project pipeline efficiently.

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Top 5 Obstacles faced by Beginners in Machine Learning

Many learners want to master Machine Learning and don’t know where to start. It seems like a formidable task, especially if one lacks a thorough background. This article will discuss some of the factors that can be obstacles in learning machine learning. Working around these obstacles can help us master and develop a long-term interest in this subject.

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Step by Step Guide to Implement Machine Learning Projects

In Machine Learning solutions, we need to have the most coordination between technology and business verticals. For any Machine Learning project from business experts, there are mainly seven different verticals or phases it has to pass. All of these seven verticals are mentioned in the image above.

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Time Series Forecasting Using Machine Learning

In Machine Learning, Time Series Forecasting refers to the use of statistical models to predict future values using the previously recorded observations.

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Pre-processing of Time Series Data In Machine Learning

Time series data is found everywhere, and to perform the time series analysis, we must preprocess the data first. Time Series preprocessing techniques have a significant influence on data modelling accuracy.

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Bias-Variance Tradeoff in Machine Learning

Bias, Variance, and Bias-Variance tradeoff are the most popular terms in machine learning and the most frequent questions asked in machine-learning interviews.

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Word Vector Encoding: Make Machines Understand Text

Computers only understand numbers, not text. So we need to convert our text into vectors using vector encoding.

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Pre-processing of Text Data in Machine Learning Part 1

Text data pre-processing ensures optimal results when executed properly. Fortunately, Python has excellent support of NLP libraries such as NLTK, spaCy, and Gensim to ease our text analysis.

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Difference between Artificial Intelligence and Machine Learning

Artificial Intelligence and Machine Learning are the most famous buzzwords in the technical industries. Generally we use them as synonyms but in actual it is not.

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Logistic Regression in Machine Learning

Logistic Regression is one of the most used machine learning algorithms in industry. It is a supervised learning algorithm where the target variable should be categorical, such as positive or negative, Type A, B, or C, etc. We can also say that it can only solve the classification problems. Although the name contains the term "regression", it is only used to solve the classification problem.

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Linear Regression

Linear Regression is a supervised machine learning algorithm used to solve regression problems.

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Car Resale Value Prediction Using Random Forest Regressor

Machine Learning has become a tool used in almost every task that requires estimation. Companies like Cars24 and Cardekho.com uses Regression analysis to estimate the used car prices. So we need to build a model to estimate the price of used cars. The model should take car-related parameters and output a selling price.

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Top Misconceptions in Machine Learning

In this article, we will be discussing those 10 most common misconceptions that are so popular that every one of us must have come across at least once in our ML journey.

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How exactly machine learns in Machine Learning?

In this article, we will try to find the answer to another most critical question in machine learning and artificial intelligence - How exactly the machine learns?

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Machine Learning Glossary: A-2-Z Terms In Machine Learning

This is a glossary of Machine Learning terms commonly used in the industry. We will add more terms related to machine learning, data science, and artificial intelligence in the coming future. Meanwhile, if you want to suggest adding more terms, please let us know.

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E-mail spam and non-spam filtering using Machine Learning

K-NN implementation and Gmail, Yahoo, and Outlook case studyIn 2019, on average, every person was receiving 130 emails each day, and overall, 296 Billion emails have been sent in that year.

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