Tech learning roadmaps…

[dallas_ear_rings]

  On 4/21/2023 at 1:29 AM, AnotherTeluguBidda said:

https://dzone.com/articles/jλvλ-8-a-comprehensive-look
 

Under the hood of java lambda and streams. Kudos to this unknown author.

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Rollercoaster ekki diginattu kallu thiruguthunnayi

[AnotherTeluguBidda]

Yeah better read by parts 

 

https://dzone.com/articles/jλvλ-8-a-comprehensive-look-part-11-lambdas-under

 

https://dzone.com/articles/jλvλ-8-a-comprehensive-look-part-12-insight-into-s

[dasari4kntr]

 

 

 

https://drive.google.com/file/d/1Aqdsi2x_QmMnTnV0jB-g-bvMp-BgCvpw/view

 

𝗛𝗶𝘀𝘁𝗼𝗿𝘆 𝗢𝗳 𝗖# 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 During more than 20 years of development, we saw 11 versions of the C# language. Every version gave us some new and interesting features. Here is a brief overview of those features:

𝗖# 𝟭.𝟬 released with .NET 1.0 and VS2002 (January 2002).

𝗖# 𝟭.𝟮 released with .NET 1.1 and VS2003 (April 2003). The first version is called Dispose on IEnumerators which implemented IDisposable.

𝗖# 𝟮.𝟬 released with .NET 2.0 and VS2005 (November 2005). Major new features: generics, anonymous methods, nullable types, and iterator blocks.

𝗖# 𝟯.𝟬 released with .NET 3.5 and VS2008 (November 2007). Major new features: lambda expressions, extension methods, expression trees, anonymous types, implicit typing (var), and query expressions.

𝗖# 𝟰.𝟬 released with .NET 4 and VS2010 (April 2010). Major new features: late binding (dynamic), delegate and interface generic variance, more COM support, named arguments, tuple data type, and optional parameters.

𝗖# 𝟱.𝟬 released with .NET 4.5 and VS2012 (August 2012). Major features: async programming and caller info attributes.

𝗖# 𝟲.𝟬 released with .NET 4.6 and VS2015 (July 2015). Enabled by Roslyn. Features: initializers for automatically implemented properties, using directives to import static members, exception filters, element initializers, await in a catch, and finally, extension Add methods in collection initializers.

𝗖# 𝟳.𝟬 released with .NET 4.7 and VS2017 (March 2017). Major new features: tuples, ref locals and ref return, pattern matching (including pattern-based switch statements), inline out parameter declarations, local functions, binary literals, digit separators, and arbitrary async returns.

𝗖# 𝟳.𝟭 released with VS2017 v15.3 (August 2017). New features: async main, tuple member name inference, default expression, and pattern matching with generics.

𝗖# 𝟳.𝟮 released with VS2017 v15.5 (November 2017). New features: private protected access modifier, Span<T>, aka interior pointer, aka stackonly struct, and everything else.

𝗖# 𝟳.𝟯 released with VS2017 v15.7 (May 2018). New features: enum, delegate, and unmanaged generic type constraints. ref reassignment.

𝗖# 𝟴.𝟬 released with .NET Core 3.0 and VS2019 v16.3 (September 2019). Major new features: nullable reference-types, asynchronous streams, indices and ranges, readonly members, using declarations, default interface methods, static local functions, and enhancement of interpolated verbatim strings.

𝗖# 𝟵.𝟬 released with .NET 5.0 and VS2019 v16.8 (November 2020). Major new features: init-only properties, records, with-expressions, data classes, positional records, top-level programs, and improved pattern matching.

𝗖# 𝟭𝟬.𝟬 released with .NET 6.0 (November 2021). Major new features: record structs, struct parameterless constructors, interpolated string handlers, global using directives, file-scoped namespace declarations, extended property patterns, const interpolated strings, and more.

𝗖# 𝟭𝟭.𝟬 released with .NET 7.0 (November 2022). Major new features: file-scoped types, generic math support, auto-default structs, pattern match Span<char> on a constant string, extended nameof scope, UTF-8 string literals, required members, ref fields, and scoped ref, raw string literals, and more. What features do you use the most?

[Spartan]

https://sharats.me/posts/shell-script-best-practices/

[VictoryTDP]

  On 5/2/2023 at 9:32 AM, Spartan said:

https://sharats.me/posts/shell-script-best-practices/

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Google style guide kooda good resource to follow for bash 

[SwamyRaRa]

@dasari4kntr @prince @Sarvapindi others…
Post Bigdata learning path with some links for training… thanks 

[MiryalgudaMaruthiRao]

  On 5/12/2023 at 11:35 AM, SwamyRaRa said:

@dasari4kntr @prince @Sarvapindi others…
Post Bigdata learning path with some links for training… thanks 

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+69

[SwamyRaRa]

  On 5/16/2023 at 3:33 PM, MiryalgudaMaruthiRao said:

+69

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69

[Paamu]

@dasari4kntr you all right. E madya no activity. 

[dasari4kntr]

  On 5/12/2023 at 11:35 AM, SwamyRaRa said:

@dasari4kntr @prince @Sarvapindi others…
Post Bigdata learning path with some links for training… thanks 

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https://drive.google.com/drive/u/0/folders/16IU5eieoZBqf0hOfQiCGmIxqvQfpxLRB?fbclid=IwAR2QBcrO-LcQ0yUhRkhFRoGE3J5PMoPf9f6S30AsndUFBHGvVUkFa2WBIGo

[dasari4kntr]

  On 5/21/2023 at 1:11 AM, Paamu said:

@dasari4kntr you all right. E madya no activity. 

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yeah...konchem time off teesukunna bro...

 

[dasari4kntr]

FULL Materials...

 

https://drive.google.com/drive/u/0/folders/1if09a9QyNfBRlAKey7If5preZ3BswudZ?fbclid=IwAR2QBcrO-LcQ0yUhRkhFRoGE3J5PMoPf9f6S30AsndUFBHGvVUkFa2WBIGo

 

 

 

 

 

 

 

[SwamyRaRa]

  On 5/22/2023 at 2:20 PM, dasari4kntr said:

https://drive.google.com/drive/u/0/folders/16IU5eieoZBqf0hOfQiCGmIxqvQfpxLRB?fbclid=IwAR2QBcrO-LcQ0yUhRkhFRoGE3J5PMoPf9f6S30AsndUFBHGvVUkFa2WBIGo

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Thanks bro 

[dasari4kntr]

https://microsoft.github.io/Data-Science-For-Beginners/#/

 

Data Science For Beginners: Roadmap - Sketchnote by @nitya

Lesson Number	Topic	Lesson Grouping	Learning Objectives	Linked Lesson	Author
01	Defining Data Science	Introduction	Learn the basic concepts behind data science and how it’s related to artificial intelligence, machine learning, and big data.	lesson video	Dmitry
02	Data Science Ethics	Introduction	Data Ethics Concepts, Challenges & Frameworks.	lesson	Nitya
03	Defining Data	Introduction	How data is classified and its common sources.	lesson	Jasmine
04	Introduction to Statistics & Probability	Introduction	The mathematical techniques of probability and statistics to understand data.	lesson video	Dmitry
05	Working with Relational Data	Working With Data	Introduction to relational data and the basics of exploring and analyzing relational data with the Structured Query Language, also known as SQL (pronounced “see-quell”).	lesson	Christopher
06	Working with NoSQL Data	Working With Data	Introduction to non-relational data, its various types and the basics of exploring and analyzing document databases.	lesson	Jasmine
07	Working with Python	Working With Data	Basics of using Python for data exploration with libraries such as Pandas. Foundational understanding of Python programming is recommended.	lesson video	Dmitry
08	Data Preparation	Working With Data	Topics on data techniques for cleaning and transforming the data to handle challenges of missing, inaccurate, or incomplete data.	lesson	Jasmine
09	Visualizing Quantities	Data Visualization	Learn how to use Matplotlib to visualize bird data 🦆	lesson	Jen
10	Visualizing Distributions of Data	Data Visualization	Visualizing observations and trends within an interval.	lesson	Jen
11	Visualizing Proportions	Data Visualization	Visualizing discrete and grouped percentages.	lesson	Jen
12	Visualizing Relationships	Data Visualization	Visualizing connections and correlations between sets of data and their variables.	lesson	Jen
13	Meaningful Visualizations	Data Visualization	Techniques and guidance for making your visualizations valuable for effective problem solving and insights.	lesson	Jen
14	Introduction to the Data Science lifecycle	Lifecycle	Introduction to the data science lifecycle and its first step of acquiring and extracting data.	lesson	Jasmine
15	Analyzing	Lifecycle	This phase of the data science lifecycle focuses on techniques to analyze data.	lesson	Jasmine
16	Communication	Lifecycle	This phase of the data science lifecycle focuses on presenting the insights from the data in a way that makes it easier for decision makers to understand.	lesson	Jalen
17	Data Science in the Cloud	Cloud Data	This series of lessons introduces data science in the cloud and its benefits.	lesson	Tiffany and Maud
18	Data Science in the Cloud	Cloud Data	Training models using Low Code tools.	lesson	Tiffany and Maud
19	Data Science in the Cloud	Cloud Data	Deploying models with Azure Machine Learning Studio.	lesson	Tiffany and Maud
20	Data Science in the Wild	In the Wild	Data science driven projects in the real world.	lesson	Nitya

[dasari4kntr]