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Mastering Data Science concepts and methodologies is crucial for success in the field. 360DigiTMG offers comprehensive courses that cover essential techniques and tools, empowering you to analyze data effectively and make data-driven decisions.
by Mr. Bharani Kumar 7937
A crucial component of the data is data that has been gathered across intervals of time that are equally spaced apart.
by Mr. Bharani Kumar 6672
The nonlinear pattern will not be captured by the mere existence of hidden layers.
by Mr. Bharani Kumar 7698
The goal of artificial intelligence is to simulate the human brain.
by Mr. Bharani Kumar 7041
In order to simulate biological neural networks, artificial neural networks are utilised.
by Mr. Bharani Kumar 7619
Almost every learning job, including classification and numerical prediction, may be used with SVMs.
by Mr. Bharani Kumar 7726
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 6248
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.
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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 8394
A machine learning method called Naive Bayes is based on the probability principle.
by Mr. Bharani Kumar 7799
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.
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The set of error functions below can be used to assess the model if the output variable 'Y' is continuous.
by Mr. Bharani Kumar 5654
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 9845
Analyzing unstructured Text data by generating structured data in key-value pair form.
by Mr. Bharani Kumar 6230
A distinct sort of data, known as network data or graph data, necessitates a different kind of analysis.
by Mr. Bharani Kumar 4862
'Users' are typically the rows in the data utilised for the analysis, and 'Items' will be the columns.
by Mr. Bharani Kumar 6680
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 5738
Feature extraction of input variables from hundreds of variables is known as Dimensionality Reduction.
by Mr. Bharani Kumar 6036
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 4369
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 3328
Standardize or Normalize the variables before calculating the distance if the variables scale or are of different units.
by Mr. Bharani Kumar 4837
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 3419
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 3653
The goal of this stage is to locate any potential data mistakes, flaws, or problems.
by Mr. Bharani Kumar 3833
Univariate Analysis - Analysis of a single variable is called Univariate Analysis.
by Mr. Bharani Kumar 7730
Other names for data cleaning include data preparation, data organisation, munging, and data wrangling.
by Mr. Bharani Kumar 8023
Cross Industry Standard Process for Data Mining. Articulate the business problem by understanding the client/customer requirements
by Mr. Bharani Kumar 5524
Definition of Artificial Intelligence, Data Science, Data Mining, Machine Learning, Deep Learning, Reinforcement Learning (RL)
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