data science Everything about Sample Size Sample size refers to the number of individual observations or data points collected from a population for a specific study or analysis.
Machine Learning (ML) Cluster Sampling Cluster sampling is a probabilistic sampling approach wherein the population is divided into clusters, and a random subset of clusters is chosen for examination.
data science Avoid these 5 Mistakes as a new Data Scientist In this article at OpenGenus, we have explored 5 common mistakes one make at their first job as a Data Scientist fresh out of School. We wrap up with 5 tips as well.
data science Unleashing the Power of APIs in Your Data Science Projects - 3 APIs You Can Master in Minutes Imagine you're a data scientist or a developer, and you're about to embark on a new project. You're excited, but there's a problem - you need data, lots of it, and from various sources.
data science Product based Mock Interview for Data Science In this article at OpenGenus, we will get familiarized with the flow of a product-based interview round.
data science 14 Data Visualization Techniques in Data Science In the world of data science where considerable volumes of information are generated and analyzed, communicating processed insights becomes vital. Data visualization transcends complexity barriers by turning raw data into useful information at different levels for various audiences.
Machine Learning (ML) 9 Advantages and 10 disadvantages of Naive Bayes Algorithm In this article, we'll talk about some of the key advantages and disadvantages of Naive Bayes algorithm.
data science Getting started with Data Science Every day in this world data is generating at the rate of 2.5 quintillion bytes per second. The field of Data Science tries to explore the insights we can gather from the data how can we predict the future or how one organization can improve its efficiency by acting on that data.
data science Data Wrangling In this article, we have explored the concept of Data Wrangling which is a critical process/ phase in Data Science. We have explored the tools used for Data Wrangling as well.
data science Data Science Cheatsheet / List of all Data Science topics This is the most complete Data Science Cheatsheet which you should follow to revise all Data Science concepts within 30 minutes and get ready for Interviews and stay in form.
List of Interview Questions Culture Fit interview for Data Science job [Mock] In this article, we will get to know the flow of a culture fit interview for a Data Science job and some pointers on how you could answer the questions asked.
data science How is Deep Learning used for Data Science tasks? In this article, we will see how deep learning is used in Data Science.
data science Project ideas for Data Science In this article, we will get to know some ideas for data science projects.
data science Python questions for Data Science interviews We will discuss a basics of Python here as importance of Python for data science cannot be emphasized enough.
data science Different types of Hypotheses In this article, we will get to know about the various types of hypotheses in statistics.
data science Advanced interview questions on Data Science In this article, we have discussed 35 advanced data science questions asked in interviews.
data science Different Datasets available In this article, we will take a look at the various datasets available that can be used for different problems.
data science Sites to find different datasets In this article, we will see some of the data sources from where we can download and use datasets for free for our data science projects.
data science AO* algorithm AO* algorithm is a best first search algorithm. AO* algorithm uses the concept of AND-OR graphs to decompose any complex problem given into smaller set of problems which are further solved.
Natural Language Processing (NLP) Types of NLP models Natural Language Processing (NLP) refers to a branch of Artificial Intelligence (AI) in Computer Science that gives computers the ability to analyze and interpret human language.
data science F Test F-tests get their name from the F test statistic, which was named after Sir Ronald Fisher. The F-statistic is just a two-variance ratio. Variances are a metric for dispersion, or how far the data deviates from the mean. Greater dispersion is shown by higher values.
data science Time Series Classification In this article, we will learn about a beginner-level approach to time series classification.
data science Fuzzy Relations, Propositions, Implications and Inferences In this article, we will first learn about fuzzy relations and the different types of operations that can be performed on them. Then, we will learn about the truth values of fuzzy propositions, about fuzzy implications or if-then rules.
data science Introduction to Feature Engineering In this article, we will be learning about an important step in the machine learning process: feature engineering.
Machine Learning (ML) Performance Comparison of Different Models and Data Preprocessing Techniques In this article, we will be comparing the performance of different data preprocessing techniques (specifically, different ways of handling missing values and categorical variables) and machine learning models applied to a tabular dataset.