Data Science Digital Book
by Mr. Bharani Kumar 6595
A crucial component of the data is data that has been gathered across intervals of time that are equally spaced apart.
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by Mr. Bharani Kumar 5706
The nonlinear pattern will not be captured by the mere existence of hidden layers.
by Mr. Bharani Kumar 6439
The goal of artificial intelligence is to simulate the human brain.
by Mr. Bharani Kumar 5838
In order to simulate biological neural networks, artificial neural networks are utilised.
by Mr. Bharani Kumar 6328
Almost every learning job, including classification and numerical prediction, may be used with SVMs.
by Mr. Bharani Kumar 6162
Predicts the probability of the outcome class. The algorithm finds the linear relationship between the independent variables and a link function of these probabilities.
by Mr. Bharani Kumar 5238
Ordinary Least Squares Technique to find the best fit line. The best fit line is the line which has minimum square deviations from all the data points to the line.
by Mr. Bharani Kumar 7766
Decision Trees are Nonparametric hierarchical model, that works on a divide & conquer strategy, a rule-based algorithm that works on the principle of recursive partitioning.
by Mr. Bharani Kumar 6785
A machine learning method called Naive Bayes is based on the probability principle.
by Mr. Bharani Kumar 6768
KNN is based on the calculating distance among the various points. The distance can be any of the distance measures such as Euclidean distance discussed in previous sections.
by Mr. Bharani Kumar 2749
The set of error functions below can be used to assess the model if the output variable 'Y' is continuous.
by Mr. Bharani Kumar 4801
Steps based on Training & Testing datasets - Get the historical/past data needed for analysis which is the output of data cleansing.
by Mr. Bharani Kumar 9022
Analyzing unstructured Text data by generating structured data in key-value pair form.
by Mr. Bharani Kumar 5126
A distinct sort of data, known as network data or graph data, necessitates a different kind of analysis.
by Mr. Bharani Kumar 4285
'Users' are typically the rows in the data utilised for the analysis, and 'Items' will be the columns.
by Mr. Bharani Kumar 5378
The same concept underlies Relationship Mining, Market Basket Analysis, and Affinity Analysis: how are two entities connected to one another and is there any reliance between them.
by Mr. Bharani Kumar 4691
Feature extraction of input variables from hundreds of variables is known as Dimensionality Reduction.
by Mr. Bharani Kumar 4953
Agglomerative technique (top-down hierarchy of clusters) or Divisive technique (bottom-up hierarchy of clusters) are other names for hierarchical clustering.
by Mr. Bharani Kumar 3796
Similar records to be grouped together. High intra-class similarity, Dissimilar records to be assigned to different groups. Less inter-class similarity
by Mr. Bharani Kumar 2846
Standardize or Normalize the variables before calculating the distance if the variables scale or are of different units.
by Mr. Bharani Kumar 4319
If the outcome variable 'Y' in the historical data is known, then supervised learning tasks are applied to the historical data. Predictive modelling and machine learning are other names for supervised learning.
by Mr. Bharani Kumar 2883
Feature Extraction and Feature Engineering are other names for attribute generation. Try to use domain expertise to create more insightful derived variables from the provided variables.
by Mr. Bharani Kumar 3093
The goal of this stage is to locate any potential data mistakes, flaws, or problems.
by Mr. Bharani Kumar 3287
Univariate Analysis - Analysis of a single variable is called Univariate Analysis.
by Mr. Bharani Kumar 6305
Other names for data cleaning include data preparation, data organisation, munging, and data wrangling.
by Mr. Bharani Kumar 7074
Cross Industry Standard Process for Data Mining. Articulate the business problem by understanding the client/customer requirements
by Mr. Bharani Kumar 4933
Definition of Artificial Intelligence, Data Science, Data Mining, Machine Learning, Deep Learning, Reinforcement Learning (RL)
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