Data Science and AI Quest

This technical blog is my own collection of notes , articles , implementations and interpretation of referred topics in coding, programming, data analytics , data science , data warehousing , Cloud Applications and Artificial Intelligence . Feel free to explore my blog and articles for reference and downloads . Do subscribe , like , share and comment ---- Vivek Dash

Monday, July 12, 2021

Infographic Note with questions and answers on the concepts of MinMaxScaler function , Standard Scaler Function , Normalisation , Standardisation in Statistical Analysis

at July 12, 2021 No comments:

Email This BlogThis!Share to X Share to Facebook Share to Pinterest

Labels: ai, algorithms, artificial intelligence, data analytics, data exploration, data science, Inferential analysis, machine learning, minmaxscaler, normalisation, standardisation, standardscaler

Infographic Note on Correlation Analysis using corr() function over a Pandas dataframe in Python

at July 12, 2021 No comments:

Email This BlogThis!Share to X Share to Facebook Share to Pinterest

Labels: ai, algorithms, artificial intelligence, correlation, data analytics, data exploration, data science, dataframe, Inferential analysis, interpretation, machine learning, numpy, pandas, python, SciPy, summary, testing

Infographic Note on Correlation Analysis of numerical attributes of a Pandas Dataframe in Python

at July 12, 2021 No comments:

Email This BlogThis!Share to X Share to Facebook Share to Pinterest

Labels: ai, algorithms, artificial intelligence, correlation, data analytics, data exploration, data science, dataframe, heatmap, Inferential analysis, machine learning, numpy, pandas, python, SciPy, summary, testing

Infographic Note on Python Code Analysis of a Sample Outliers Detection function over a numerical attribute in a pandas dataframe

at July 12, 2021 No comments:

Email This BlogThis!Share to X Share to Facebook Share to Pinterest

Labels: ai, algorithms, artificial intelligence, data analytics, data exploration, data science, function, Inferential analysis, machine learning, numpy, outliers, pandas, python, SciPy, summary, testing

Infographic Note on Outliers Detection , finding Inter-Quartile ranges and Interpreting Box-Plot diagrams over Pandas Dataframe in Python

at July 12, 2021 No comments:

Email This BlogThis!Share to X Share to Facebook Share to Pinterest

Labels: ai, algorithms, artificial intelligence, boxplot, data analytics, data exploration, data science, Inferential analysis, inter-quartile range, machine learning, numpy, outliers, pandas, python, SciPy, summary

Infographic Note on steps to perform Count , filter , group and aggregate numerical values over a dataset using Numpy and Pandas in Python using Jupyter Notebook IDE

at July 12, 2021 No comments:

Email This BlogThis!Share to X Share to Facebook Share to Pinterest

Labels: aggregate, ai, algorithms, artificial intelligence, data analytics, data exploration, data science, filter, group, hypothesis, machine learning, numpy, pandas, python, SciPy, summary, t-test, testing, value_count

Infographic Note on steps to formulate and perform a Hypothesis Test using Numpy , Pandas and Scipy Libraries of Python

at July 12, 2021 No comments:

Email This BlogThis!Share to X Share to Facebook Share to Pinterest

Labels: ai, algorithms, artificial intelligence, data analytics, data exploration, data science, hypothesis, Inferential analysis, machine learning, numpy, pandas, python, SciPy, summary, t-test, testing

Newer Posts Older Posts Home

Subscribe to: Posts (Atom)

One Hot Encoding and Dummy Variables Generation upon a dataframe | Scenario - Perform One-Hot Encoding upon Un-Ordered Data in a sample dataframe and generate One-hot encoded feature variables | Conceptual Infographic Note

Data Pre-processing in Machine Learning - All the constituent steps which are part of a Machine Learning Project ( infographic notes )
Infographic Notes on the concept of Linear Regression - What is Regression Analysis ?
One Hot Encoding and Dummy Variables Generation upon a dataframe | Scenario - Perform One-Hot Encoding upon Un-Ordered Data in a sample dataframe and generate One-hot encoded feature variables | Conceptual Infographic Note

Search This Blog

Home

Labels

1D indexing abstract Accuracy adjustment advantages aggregate AGI ai algebra algorithm algorithms alternative amazon analysis analytics ANN anonymous ANOVA append application arguments Arithmetic Range arpanet Array Arrays Artificial General Intelligence artificial intelligence at&t Australia Autobiography of a Yogi AutoML average aws azure bangalore banking application basic project beginning bengaluru best practices best state bhubaneswar biases big data Big Data Analytics bill generation binomial bitcoin blue-print boxplot bubble sort C4.5 calculation calculation.tutorial calculus Canada CART case study categorical CDN challenges character chennai chi-squared distribution china chronological class classes classification classifier cloning cloud cloud applications code analysis coding coefficients collection commerce compaq computer game computer science computing concatenation concept Concepts condition considerations construct copying corona corpus linguistics correlation cost aspect cost function cost-effectiveness covariance covid-19 cross validation cryptocurrency cybersecurity daigonal matrix data data access data analysis data analytics data engineering data exploration data mining Data Modelling Data Preprocessing Data Retrieval data science data sources data structure data types data velocity data volume database dataframe dbms debugging decision making decision tree deep learning defining definition delh delhi Demand Engineering dependent variables design development deviation dictiionaries dictionary difference Digitisation dijkstra disadvantages disctionary as database distribution dump dumps eample elections email spam and malware filtering encoding engineer english ensemble ensembling entopy Epoch errors ethereum evolution example experiment explanation expressions FaaS feature support features filter filtering find-s findall function findall() finding fixers flexibility forecasting frequency func function functions game gcp generaliser generator geographical Germany github google GPU gradient boosting greedy algorithms grid search group guess a number guessing game hadoop hangman hardware acceleration hdfs heatmap heterogenuous data history hive homogenuous data HP huffman encoding hyper parameter hypothesis ID3 image recognition images implementation implementations important independent variables indexing india inductive Inferential analysis inflection word infographic information gain information technology inner class Input installation instance instances integrity constraints inter-quartile range internet interpretation interview inverse document frequency iteration Japan jargon job join function jupyter notebook k-means kaggle keras knn kolkata kolkate kwargs lambda lambda expressions Latency learning learning rate lemmatization letter guessing game limitations linear regression linters list list elements litecoin LMS load loads logic logistic regression loops lstrip machine learning madlibs manipulation mathematics Matrices mcnemar test mean median member classes method method local class method overloading methods microsoft minmaxscaler mode modelling module Monitoring and Auto-Remediation morphological analysis multinomial mumbai Mutability N-dimensional naive bayes natural language processing negative Netflix Animation neural networks neurosciience new thread news NLP nltk nominal data normalisation nosql nosql databases notation note notes null numpy Object Objects octave odisha on-demand one-hot encoding Onehotencoder online fraud detection OOPS Open Connect operators optimisation ordering ordinal ordinal data outlier deletion outliers Output output analysis overfitting overridden overriding overview overwritten package pandas pandemic parent string pattern pattern matching pattern programming pca phone number verification physical Pickle pickling pipeline pipelining plot diagrams porter portstemmer POS-tagging positional indexing poster practices Prediction probability problem problems procedure product recommendation program programming project pseudo code python pytorch Q&A qualitiative quantitative question question and answer question of the day questions R language random module ratios rdbms redundancy constraints Regression regular expressions reinforcement learning reliability rental representation reserved instances resources revision roadmap rock-paper-scissors Rstrip Russia Saas sample scalability scalars Scientific Experimentation scikit-learn SciPy Search search engines seasonality security seed function self-driving cars sent_tokenize sentiment analysis Serialization server;ess serverless services set shape shopping cart significance sklearn software sorting source code speeach recognition sql standardisation standardscaler statistics stem Stemming steps stock stockmarket stopwords filtering storage Streams stress string string manipulation strings strip structured data sub-string substitution summary supervised survey svm swap swapcase syntax t-test target target learning task tasks techgig technique techniques technology temporary variable tensorflow term frequency test testing text pre-processing text processing tf-idf theorem thread thread handling time series timepass tokenisation Tools total bill trade traffic prediction training trend trivia tuples twitter sentimental analysis Two-way Anova types UK underfitting unstructured data unsupervised USA usage uttar pradesh vaccine value_count variables variant word vector VFX Information Security Video Encoding virtual personal assistant Visualisation vocab vocabulary VOD web frameworks weights wellness west bengal word game word meaning word_tokenize wordNetLemmatizer wrapper xgboost z-score zeroes Zip function

About Me

Vivek Dash

View my complete profile

Blog Archive

August 2021 (3)
July 2021 (71)
June 2021 (143)
May 2021 (271)
April 2021 (42)
March 2021 (44)
February 2021 (102)
January 2021 (33)
December 2020 (28)
September 2020 (420)

Report Abuse

Theme images by luoman. Powered by Blogger.