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MySQL

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Scalability

Reliability…what is that? “continuing to work correctly, even when things go wrong.” The things that can go wrong are called faults, and systems that anticipate faults and can cope with them are called fault-tolerant or resilient. The former term is slightly misleading: it suggests that we could make a system tolerant of every possible kind of fault, which in reality is not feasible. If the entire planet Earth (and all servers on it) were swallowed by a black hole, tolerance of that fault would require web hosting in space—good luck getting that budget item approved. So it only makes sense to talk about tolerating certain types of faults. Note that a fault is not the same as a failure. A fault is usually defined as one component of the system deviating from its spec, whereas a failure is when the system as a whole stops providing the required service to the user. It is impossible to reduce the probability of a fault to zero; therefore it is usually best to design fault-tolerance mechanisms that prevent faults from causing failures.

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Writing secure python applications

Table of contents Injection Attacks SQL Injection XML Injection Command Injection Broken authentication & session management Session fixation Use of Insufficiently random values Cross site scripting Reflected XSS Persistent XSS Document Object Model (DOM) Based XSS Insecure direct object references Directory (Path) Traversal Security Misconfiguration Privileged Interface Exposure Leftover debug code Sensitive data exposure Authentication credentials in URL Session Exposure within URL User Enumeration Missing function level access control Horizontal Privilege Escalation Vertical privileage Escalation Cross site request forgery Cross site request forgery(POST) Cross site request forgery(GET) Click Jacking Unvalidated redirects & Forwards Insecure URL redirect

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System design

Table of contents Software Design Theoritical concepts - Introduction CRC Card Four concepts revolving around OOP Coupling & Cohesion Separation of concerns SOLID The Single Responsibility Principle The Open Closed Principle The Liskov Substitution Principle The Interface Segretation Principle The Dependency Inversion Principle Class Diagrams Tool to draw UML UML class diagram rules Sample UML Diagrams examples Object oriented cheat-sheet References

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Shipping machine learning modules in a single executable

You have done all your research, prototyped it, optimize it and now you are ready to ship it. This post not only focusses on shipping machine learning modules but python based codebases in general. How do you ship ? Expose an API Package your code in a single executable

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Using Anaconda in CI/CD pipeline

To successfully build the pipeline, it was required to automate all the yes invocation while executing Anaconda sh file. I did by invoking sh file with -b option bash Anaconda2-5.0.1-Linux-x86_64.sh -b

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Language Modelling in NLP

What is Language Modelling ? Language modeling in very simple terms is the task of assigning a probability to sentences in a language. Besides assigning a probability to each sequence of words, the language models also assigns a probability for the likelihood of a given word (or a sequence of words) to follow a sequence of words.

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All you need to know about Word2vec

Why is word embedding needed? Purpose is to create a representation for words that capture their meanings, semantic relationships and the different types of contexts they are used in. And all of these are implemented by using Word Embeddings or numerical representations of texts so that computers may handle them. What is word embedding ? In very simplistic terms, Word Embeddings are the texts converted into numbers and there may be different numerical representations of the same text. But before we dive into the details of Word Embeddings, the following question should be asked – Why do we need Word Embeddings?

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All you need to know about BOW

Feature Extraction from texts using Bag of words The bag of words model ignores grammar and order of words. ‘All my cats in a row’, ‘When my cat sits down, she looks like a Furby toy!’, Breaking down the given sentences into words and assigning them each a unique ID

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