Forem: Snehal Adbol

What is PyTorch? And why you should learn it?

Snehal Adbol — Sat, 10 Dec 2022 08:13:25 +0000

What is PyTorch?

PyTorch is an open-source deep-learning library for Python. It is developed by Facebook's AI research group and is widely used in the research and development of deep learning models.

Pytorch is focused on providing high-level APIs for building and training complex neural network models and includes support for automatic differentiation and distributed training. Pytorch is often used for developing and training large, state-of-the-art models for applications such as computer vision and natural language processing.

Why learn PyTorch?

One of the key reasons to learn PyTorch is its ability to perform computations on tensors, which are multi-dimensional arrays used for storing and processing data in machine learning algorithms. PyTorch includes a set of high-level APIs that make it easy to build and train complex neural network models and allows developers to perform computations on tensors in a dynamic, flexible, and efficient way.

Another reason to learn PyTorch is its support for automatic differentiation, a technique used to compute the gradient of a mathematical function. This is a crucial feature for training deep learning models, as it allows the models to learn from data by adjusting the model parameters to minimize a loss function. PyTorch's support for automatic differentiation enables developers to easily implement and optimize complex neural network architectures.

In addition to its core features, PyTorch includes various tools and libraries that make it easier to develop and deploy machine learning models. This provides support for distributed training support, allowing developers to train large models on multiple GPUs or machines. PyTorch also contains libraries for computer vision, natural language processing, and other applications of machine learning.

Closing notes

Overall, learning PyTorch can be a valuable skill for anyone interested in working with deep learning or artificial intelligence. PyTorch is a powerful and popular library and is widely used by researchers and developers. By learning PyTorch, you can gain the skills and knowledge needed to develop and deploy cutting-edge machine learning models.

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What is CI/CD, and why is it important?

Snehal Adbol — Sun, 14 Aug 2022 07:09:00 +0000

One of the worst messages a developer might get in Git is "Merge conflict." You've worked on a feature for hours, and your code is now flawless. However, another developer altered the same section of the file, so you need to examine the differences, decide which adjustments to preserve, and run all your tests once more before attempting to merge again.

A merge conflict that occasionally arises is only a minor annoyance. However, picture yourself as a member of a highly integrated team that is tasked with releasing new features quickly. Multiple developers must collaborate on the same file due to the timeframe. Merge conflicts exist if everyone pushes their contributions at the same time. This kind of mistake is not only annoying but also ineffective.

Thus, The CI/CD methodology was developed To address this issue and accelerate development. Let's examine this strategy, its significance, and the tools you may use to put it into practice.

What is CI/CD?

Continuous integration and continuous delivery are abbreviated as CI and CD, respectively. In its basic form, continuous integration (CI) is a current software development process in which incremental code changes are done regularly and reliably. CI-triggered automated build-and-test stages ensure that code changes merged into the repository are stable. The code is provided swiftly and flawlessly as part of the CD process. The CI/CD pipeline in the software industry describes the automation that allows incremental code changes from developers' workstations to be delivered rapidly and reliably to production.

What is the difference between CI and CD?

Continuous Integration (CI) is a software development approach that assists developers in incorporating changes to their code into the project's main branch as frequently as feasible. It helps avoid potential integration issues and makes tracking changes easier.
Continuous Delivery (CD) is a software delivery method that assures the release of all new features, patches, and updates in a quality-controlled way. It reduces the possibility of introducing bugs into the live system.
Continuous Deployment (CD) is a software deployment method that automates the distribution of new versions of programs to selected servers. It ensures that apps are constantly available and satisfy customers' expectations.

In summary, CI is a set of practices conducted while developers produce code. In contrast, CD is a set of processes performed after the code is completed.

Why do we need CI/CD?
CI/CD streamlines integrating, releasing, and deploying software while eliminating conventional obstacles. It contributes to the more significant objective of agile methodology, which is to shorten the software development lifecycle, and to the DevOps strategy, which is to align development and operations teams.

In addition to supporting these larger goals, CI/CD enables you to:

Increased Release Rate
DevOps is about increasing the rate at which new software versions are released. A well-functioning CI/CD pipeline can assist in this goal by automating the deployment process and lowering the amount of human effort necessary. It shortens feedback loops, allowing for more testing and validation, resulting in a more reliable product.
Standardize procedures: Automating the merge, test, delivery, and deployment processes standardize the pipeline, whereas manual execution always involves the risk of human mistakes, such as running tests in the wrong order.
Reduce delivery risk: Testing each change before it is released delivers a higher quality product and a lower rate of defects in production. Customers will receive an enhanced product, and the development team will spend less time resolving urgent flaws uncovered after release.

GitHub Actions, Jenkins, GitLab, Xcode Cloud, Atlassian Bamboo, and CircleCI, are some of the popular CI/CD frameworks.

Summary

CI/CD is an effective method for ensuring the success of software development initiatives. It aids in the automation of the development and testing of code and the distribution of updates to users. However, it is crucial to remember that CI/CD does not solve all problems. Its advantages will vary based on the project and organization. I hope you found this essay informative.

Resources
spacelift.io/blog/ci-cd-pipeline

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Some Awesome APIs for your next project

Snehal Adbol — Sat, 08 Jan 2022 14:44:49 +0000

Some Awesome APIs for your next project

Several free web APIs are available to connect to your mobile app, web app, or website to add compelling functionality.

A web API is an application programming interface that may be accessed through the internet using web-specific protocols.

Here are nine APIs to create some fantastic projects:

1. The CheapShark API

CheapShark is a service that monitors the pricing of PC games on sites such as Amazon, Steam, and GamersGate and displays the best discounts to customers. Users may check for top bargains, search for the lowest price on a specific game, sign up for notifications, or browse what’s available on the site. Developers may use the CheapShark API to incorporate the site’s pricing data into their websites or apps.

link - CheapShark API

2. The Wit.AI

Turn text or speech into recognizable actions that your app/website can use.

Wit.ai is an interface for natural language processing (NLP) that converts natural language (voice or text communications) into structured data. Wit is used by developers because it streamlines creating apps and gadgets with which users can speak. Developers would have to master natural language processing methods without it. That would take too much time if you only wanted to create a simple application.

link - Wit.ai API

3. GrammarBot API

The GrammarBot API offers spelling and grammatical checks to your application. Submit the text, and you’ll get a JSON response with potential issues and suggested fixes.

link - GrammarBot API

4. Rapid API

Based only on APIs, this is a handy tool. It’s more than simply an API directory; it’s also an API marketplace. If you’ve created an API and want to charge others to use it, you can publish it on RapidAPI.

If you only want to utilize APIs, RapidAPI provides an API playground to test an API in several languages! It is pretty beneficial.

link - Rapid API

Thanks for reading!

I hope it motivates you to build more amazing projects, acquire confidence, and grow as a developer!

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Tips to improve your django skills - part 1

Snehal Adbol — Fri, 12 Nov 2021 17:40:05 +0000

makemigrations and then sqlmigrate

I only now discovered sqlmigrate and regret not having known about it before. sqlmigrate prints the SQL for your migrations, so run a fast sqlmigrate after creating a new migration. Very often, you will see that this migration is not performing any SQL migrations; for example, if you change a field, you will frequently get the following sqlmigrate output:

BEGIN;  
--  
-- Alter field name on player  
--  
COMMIT;

I recommend giving it a shot if you want to learn more about Django migration. You'll quickly figure out which modifications have an impact on your database and which don't. As a consequence, learning SQL on the go is always a good idea.

Use time zone and stop using date.today()

Most users don't worry about time zone at the start of a project, so they're content to use datetime.datetime.now() and datetime.date.today() . However, you may eventually encounter strange errors in which certain computations appear to be off by two hours or even a day.

I know what it's like to attempt to correct all these errors by making all your thousands of now() and today() calls time zone aware, because I've had to do it twice for larger applications. You'll most likely have to do them one at a time, and you'll always run into difficulties where adding a time zone later is difficult.

This is readily avoided by just using time zones all of the time. Especially because Django is so wonderful at supporting it. So, don't be frightened, and just support time zones, even if you believe you don't need them. Add the setting USE TZ = True and then always call django.utils.timezone.now() or django.utils.timezone.now().date.

More information about Django's time zones can be found here:

Adding forms to views. py

It is advised that you put all of your forms in a separate forms.py file, however since forms are merely a method of styling a view, it makes more sense to put each form at the top of its view. You will be working on the view and the form at the same time, so if your models.py becomes too cluttered, you may transfer some of your models into a second model file. That's true, your models don't all have to be in the same file.

This configuration enables you to work on both your form and your view at the same time.

Closing notes

Thank you for spending the time to read my blog post! I hope these three tips have aided you in improving your Django work. Please let me know in the comments below whether you found these strategies useful or if you've discovered even better solutions, since I'm really interested in your feedback!

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Introduction to Machine Learning

Snehal Adbol — Fri, 15 Oct 2021 09:32:33 +0000

Introduction to machine learning

Machine Learning has been a buzzword in recent years, owing to the massive quantity of data generated by applications and recent increases in computer power, and the development of better algorithms.

Machine Learning is utilized in various applications, ranging from automating monotonous operations to offering innovative insights; organizations and companies are attempting to profit. You may already be using a gadget that uses it, such as a wearable fitness tracker like Fitbit or an intelligent home assistant like Google Home. However, there are numerous additional examples of ML in action.

What is Machine Learning?

According to Arthur Samuel, machine learning techniques allow computers to learn from data and even improve themselves without being explicitly programmed.

Machine learning (ML) is a method that allows software programs to become more accurate at predicting occurrences without being explicitly programmed. The fundamental concept underlying machine learning is to develop algorithms that can take in input data and use statistical analysis to predict an output while updating results as new data becomes available.

Types of Machine Learning?

Machine learning can be classified into three types of algorithms.
Supervised Learning
Unsupervised Learning
Reinforcement Learning

Overview of Supervised Learning Algorithm

In Supervised learning, an AI system is provided with labeled data, which implies that each data point has been tagged with the correct label.
The aim is to estimate the mapping function so effectively that when you receive new input data (x), you can anticipate the output variables (Y) for that data.
For instance, we have a dataset with pictures of dogs and cats. We display the model labeled photos of dogs and cats while training it, and it learns to classify images into dogs and cats.

Types of Supervised learning

Classification: Classification is a strategy for identifying which class the dependent belongs to based on one or more independent variables. Classification is used to anticipate discrete responses.
Regression: Regression is the process of determining a model or function for separating data into continuous real values rather than classes or discrete values.

Overview of Unsupervised Learning Algorithm

Unsupervised learning uses machine learning algorithms to evaluate and cluster unlabeled information. These algorithms find hidden patterns or data groupings without the need for human involvement.

Unlike supervised learning, the data is not tagged with the correct label.

For example, Unsupervised learning can help uncover data trends to build more successful cross-selling tactics using prior purchase behavior data. Online sellers utilize this to provide appropriate add-on recommendations to customers throughout the checkout process.

Types of Unsupervised learning

Clustering: Clustering is the most significant unsupervised learning issue; like with all other problems of this type, it involves discovering a structure in a set of unlabeled data.
Association: Association rules mining is used to discover new and exciting relationships between items in a collection, a typical pattern in transactional data, or any relational database.

Overview of Reinforcement Learning

Reinforcement Learning is a feedback-based Machine Learning approach in which an agent learns how to behave in a given environment by executing actions and seeing the outcomes of those actions. The agent receives positive feedback, and for each poor action, the agent receives negative feedback or a penalty.
It is a form of dynamic programming that uses a reward and penalty system to train algorithms.

For example, RL in In healthcare is used to propose various treatment choices. While supervised learning models may be used to predict whether or not a person has an illness, RL can predict treatment choices after a person has a disease.

Essentially, by leveraging the incentives received, the agent increases its environment knowledge to choose the following action.

Summary

Machine learning (ML) is a method that allows software programs to become more accurate at predicting occurrences without being explicitly programmed.
What is Machine Learning?
According to Arthur Samuel, machine learning techniques allow computers to learn from data and even improve themselves without being explicitly programmed.

Types of Machine Learning?

Supervised learning
Unsupervised learning
Reinforcement learning

Thanks for reading!

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What is Django, and why you should learn it?

Snehal Adbol — Mon, 11 Oct 2021 08:21:50 +0000

What is Django?

Django is a web framework or backend framework used to create efficient and attractive websites or web apps quickly.
Django is built on Python, which is one of the top Programming Languages. The primary purpose of Django is to facilitate the super-fast development of backend applications.
It makes web development straightforward and fast and can help add much-advanced functionality to the website without getting into its complexity.
It also makes developing a website simple and easy using Django since it provides built-in user authentication, content administration, and sitemaps.

How does Django work?

Django follows the model-view-template (MVT) architectural pattern.
What is MVT?
Model: The model acts as the interface of your data. It is responsible for managing data. The logical data formation behind the entire application and represented by a database (commonly relational databases such as MySql, Postgres). To check more, visit – Django Model.

View: The View is the user interface. It is represented by HTML/CSS/Javascript and Jinja files. To check more, visit – Django Views.

Template: A template consists of static parts of the desired HTML output and some specific syntax that specifies how dynamic information will be added. To check more, visit – Django Templates.

Why use Django?

The Django web framework is ideal for novices since it saves time and has strong community support. It is also ideal for more experienced developers because it is open-source and has many built-in features. There is a plethora of excellent videos and material available online, making learning easy. Django is perfect for most CRUD web applications. It is also a fantastic choice for large-scale projects because it has many features. The web project you create with Django may be as basic or as sophisticated as you want it to be.

Django enables developers to create web applications that are adaptable, secure, scalable, maintainable, and manageable. All of these elements are advantageous to any web developer, but let us take a deeper look. Django can be combined with other Python modules to create a more full and sophisticated application. Django helps developers create more secure websites and handle user accounts and passwords by offering a framework that has already been correctly and thoroughly built. Without writing the entire application from scratch, developers will not make common mistakes that risk a site's security.

By default, Django protects against a wide range of typical vulnerabilities, such as SQL injection, cross-site scripting, cross-site request forgetting, and clickjacking, allowing developers to focus on developing their product.
Because it is component-based and has a naturally independent design, Django is the appropriate framework for an application that will need to scale up for growing traffic. Each component that must be updated may be modified individually, resulting in greater scalability efficiency and fewer issues.

Closing notes

Django, in my opinion, not only speeds up development but also serves as a great teaching tool for software development. Django is the first framework I learned when I first began coding.
Django has a lot of street cred because a lot of well-known companies utilize it. Here are a few examples:

Reddit
Instagram
Pinterest
Dropbox
Mozilla
Spotify

In conclusion, Django offers a wide range of use cases, such as enormous volumes of data and user interactions, as well as small-
scale applications. So, regardless of your goal, it is a safe choice to go with.

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