Forem: Rishabh Rathore

Here are some Git commands that can help you to save time and increase your productivity

Rishabh Rathore — Wed, 22 Feb 2023 13:52:36 +0000

If you don't know about it, here is a short description of git🤔 :

Git is a popular open-source distributed version control system that allows for efficient collaboration among developers and easy switching between different project versions. It can handle projects of any size with speed and efficiency and provides powerful features for tracking changes and analyzing project history.

Git init: Create an empty Git repository or reinitialize an existing one
Git Diff: Recognize changes between commits, commit and working tree, etc.
Git Status: List the new or unmodified file
Git add : Stage a file
Git add . / add * / --all: Stage all changed files at once
Git commit -a: Commit all local changes in tracked files
Git commit: Commit previously staged changes
Git commit --amend: Change the last commit
Git-log: Show commit logs
Git log --oneline: Display the log in a single line for quick reference
Git log --grep =" ": Limit the output to commits with log messages that match a pattern (regular expression)
Git checkout : Switch to a new branch and update the working directory
Git branch -d/--delete: Delete a branch
Git checkout -b - : Create and switch to a new branch
Git-revert: Revert existing commits
Git-reset: Reset the current HEAD to a specified state
Git fetch : Fetch all branches from a remote repository
Git pull : Fetch remote version of a branch and update the local branch
Git push : Push committed changes to a remote repository
Git merge : Merge the specified branch into the current branch

Use these Git commands to streamline your workflow and improve your coding experience.

Machine Learning Development Life Cycle (MLDLC/MLDC)

Rishabh Rathore — Wed, 22 Feb 2023 03:33:33 +0000

The "Machine Learning Development Life Cycle (MLDLC/MLDC)" is an approach to addressing business issues using machine learning. It involves comprehending the problem, developing a solution, transforming data, and creating a model. These distinct steps combine to form the complete machine-learning development cycle.

These are the following steps included in any machine learning project:

Business Understanding: This stage is crucial in tackling a business problem and involves gaining insight into the problem by asking relevant questions.
Data Gathering and Collection: After defining the problem, we need data to solve it. Because we don't always get the right data, we can create a data set by combining data, web scraping, or using specific APIs.
Preprocessing: In this step, the data was prepared for analysis by removing duplicates, handling missing values, converting data types, scaling and normalizing values, addressing outliers, and encoding categorical variables.
Exploratory data analysis (EDA): EDA is a method for analyzing, summarizing, and understanding the main characteristics and relationships in data.
Feature engineering and selection: This involves creating new features and selecting the most important ones for modeling, aiming to improve performance and reduce complexity. Techniques such as correlation analysis, feature importance calculations, and dimensionality reduction are used.
Model Training and Evaluation: In this stage, we try out the different kinds of machine learning models, e.g., supervised and unsupervised learning algorithms, and evaluate model performance on various parameters like the confusion matrix, accuracy, precision, recall, etc.
Model Deployment: Deploying the trained model on cloud platforms such as Heroku, GCP, or AWS to make it usable for real-world applications.
Testing: After successful deployment, evaluate the machine learning model's performance on real-world data to assess its ability to solve the target problem.
Optimize: Improve the machine learning model's performance by analyzing test results and adjusting parameters, features, or algorithms, then repeating the process as needed.

Found this post useful and learned something new?
Follow me, Rishabh

All about blockchain technology.

Rishabh Rathore — Fri, 23 Sep 2022 18:20:46 +0000

After reading this article, you have so much knowledge about the blockchain, so you can pass it on to others as well.

Before learning about blockchain technology, first learn what blockchain means.

What is blockchain?

A blockchain is a distributed system of immutable records called blocks, which are secured using cryptography. A block is a record book that contains the details of a transaction data. A distributed ledger that holds a collection of interlinked blocks along with a block hash is called a "blockchain."

Blockchian's History

It was launched only ten years ago and has the potential to replace the existing system and become the foundation of global record-keeping systems. It was created by the unknown person behind the online cash currency, bitcoin, under the pseudonym of Satoshi Nakamoto.

An overview of blockchain history:

1991
A cryptographically secured chain of blocks is described for the first time by Stuart Haber and W Scott Stornetta

1998
Computer scientist Nick Szabo works on ‘bit gold’, a decentralised digital currency

2000
Stefan Konst publishes his theory of cryptographic secured chains, plus ideas for implementation

2008
Developer(s) working under the pseudonym Satoshi Nakamoto release a white paper establishing the model for a blockchain

2009
Nakamoto implements the first blockchain as the public ledger for transactions made using bitcoin

2014
The potential of blockchain technology for other financial and collaboration transactions is studied after it is cut off from the cryptocurrency. The term "blockchain 2.0" is introduced, alluding to uses beyond cash.

The Ethereum blockchain architecture inserts computer code into the blocks to represent securities like bonds. These are referred to as smart contracts.

Technology generations of Blockchain

Nowadays, the Blockchain is growing and top global companies and various governments are testing Blockchain in the areas of Land Registry, International Trade, Global Trade and Customs, Banking, Automotive,Entertainment, Financial Services, Food & Beverages,Insurance, Oil & Gas, Pharmaceuticals, Retail, Social Media,Technology, Bond and Lending Market, Real Estate, etc.

The First Generation Cryptocurrency (Bitcoin)

Blockchain technology began When Satoshi Nakamoto published the Bitcoin whitepaper, he essentially introduced blockchain technology to the world. Back then, cryptocurrency was the only use case for the blockchain. It was a decentralised ledger that could keep a transparent, permanent record of cryptographic transactions. While blockchain has since been used in a wide range of other areas, it was designed specifically for this digital currency and to advance the goals of digital currencies .

In its earliest stages, blockchain technology set up the basic premise of a shared public ledger that supports a cryptocurrency network. Satoshi's idea of blockchain makes use of 1 megabyte (MB) blocks of information on bitcoin transactions. Blocks are linked together through a complex cryptographic verification process, forming an immutable chain. Even in its earliest guises, blockchain technology set up many of the central features of these systems.

The Second Generation - Smart Contracts (Ethereum)

Later on, the developers discovered that a blockchain could do more than just record transactions. For example, the Ethereum creators believed that assets and trust agreements potentially benefit from blockchain administration. In this sense, ethereum is the second generation of blockchain technology.

This "smart" network introduced two revolutionary concepts that completely changed our perception of blockchain technology. The first and most important concept was smart contracts. These smart contracts paved the way for the second revolution, which was blockchain as a digital ecosystem. Several developers will now be able to start their own cryptocurrency projects and applications using Ethereum's smart contract technology. Therefore, more than a cryptocurrency, Ethereum acts as a platform which developers can use to build on. It’s like the blockchain version of iOS or Android, where decentralised apps can be developed and launched.

The Third Generation - The Future(Ethereum 2.0, Cardano, Polkadot)

Scalability is one of the most pressing concerns confronting the blockchain. Transaction processing times and bottlenecking remain a problem for Bitcoin. Many new digital currencies have attempted, with various degrees of success, to modify their blockchains in order to address these challenges. Scalability is likely to be one of the most crucial advances paving the way for blockchain technology in the future. New blockchain applications are being found and implemented all the time. It's difficult to predict where these advancements will take the technology and the wider bitcoin business. Blockchain supporters are likely to find this quite exciting; from their perspective, we are living in an epochal time with an epochal technology that is still growing and unfolding.

Types of Blockchain

Based on the nature of data accessibility, blockchain can be categorised as below:

Public Blockchain: In this type of blockchain, anyone can read and submit transactions.
Private Blockchain: -In this type of blockchain, only one organisation or all subsidiary organisations within the same group are allowed to read and submit transactions.
Community/Consortium Blockchain: -In this type of blockchain, multiple groups of organisations form a consortium and are allowed to submit transactions and read transactional data.
Hybrid Blockchain: - This is a new category where any of the three (public, private, or community/consortium) blockchains can be combined to facilitate transactions. A Blockchain platform can be configured in multi-mode using Hybrid Blockchain.

It can be classified as follows based on the need for authorization to participate in Blockchain:

Permissionless Blockchain: - No prior permission is needed to participate in this type of blockchain. Everyone is allowed to participate in the verification process and can join the blockchain network with their own computational power.
Permissioned Blockchain: - To join this type of blockchain, prior permission is needed. Only authorised parties are allowed to run nodes to verify transactions in the blockchain network.
Hybrid Blockchain: - There could be a possibility that a node is participating in permissionless and permissioned blockchains together to facilitate interblockchain communication. Such a blockchain could be called a hybrid blockchain. A blockchain platform can also be configured to support permissioned and/or permissionless models.

Blockchain Characteristics

Increased Capacity : - The most remarkable aspect of this blockchain technology is that it boosts the overall network capacity. Because there are many computers working together, the total power is greater than a few of the devices where things are centralised.
Better Security:- Because there is no single point of failure, blockchain technology is regarded more secure than its contemporaries. Blockchain functions on a well-distributed network of nodes, so data is always circulated via numerous nodes, ensuring that even if one node is hacked or broken in any way, the integrity of the original data is not affected.
Immutability: - Blockchain's distributed ledger is designed in such a way that transactions can only be appended. Each block holds the hash value of the previous block. Thus, any modification in one block will generate a different hash value for the modified block. Therefore, all the next blocks in the chain will also give differenthash values.
Hash Encryption: - A blockchain uses cryptography to ensure that all the data in the blocks is kept secure from unauthorised access and is not altered. The Blockchain uses SHA-256 for encryption. SHA-256 is one of the strongest hash functions available. This cryptographic hash algorithm generates an almost unique 256-bit signature for a piece of text. Blockchains also use digital signatures to validate users.
Proof of work -Bitcoin uses a proof-of-work system. What is proof of work? It is a piece of data that's very hard to produce (meaning it takes a lot of time or costs a lot of money) but can be easily verified by others, and it satisfies specific requirements. With bitcoin, proof of work is a competition among miners who want to add a block to the blockchain—meaning they have to find the nonce value for the block by solving a mathematical puzzle.
Consensus: - Blockchain technologies are particularly effective due to the consensus algorithm. It is an essential element of every blockchain and a distinguishing feature. Simply explained, consensus is a decision-making mechanism for the network's active nodes. Here, the nodes can reach an agreement relatively quickly.

Blockchain Platform and Categorization

If you found it meaningful and you have learned something new from this, please like and share it so that it reaches the masses. Follow me on Twitter or LinkedIn, where I post content related to machine learning, data science, and tech-related things. You can also find me on Github.

References :
1.Investopedia.
2.cnbctv18
3.Icaew
4.The_Disruptive_Blockchain

10 Data Science and Machine Learning Libraries

Rishabh Rathore — Fri, 15 Oct 2021 21:14:12 +0000

1. Pandas

Pandas is a Python package that provides fast, powerful, flexible and easy to use open source data analysis and manipulation and analysis tool,built on top of the Python programming language.
In particular, it offers data structures and operations for manipulating numerical tables and time series.

Uses of Pandas

Data Structure
Data cleansing
Data filling
Data normalization
Merges and joins
Data visualization
Statistical analysis
Data inspection

2. Numpy

NumPy is a library for the Python programming language, that offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms,multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.

Uses of Numpy

Vector-Vector,Matrix-Matrix and Matrix-Vector multiplication
Reduction, statistics
Element-wise or array-wise comparisons
Linear Algebra operations
Bitwise Operators
Linear Algebra
Copying and viewing arrays
Stacking

3. SciPy

SciPy is a Python-based ecosystem of open-source software for mathematics,scientific computing and technical computing. SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.

Uses of scipy

Optimization
Linear algebra
Integration
Interpolation
Signal and Image processing

4. Matplotlib

Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python programming language and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK

Uses of Matplotlib

Histograms, Spectrograms
2D plots
Line Plot,Scatter Plot
Bar Chart,Pie Chart

5. Seaborn

Seaborn is a Python data visualization library based on matplotlib. Many data scientists prefer seaborn over matplotlib due to its high-level interface for drawing attractive and informative statistical graphics.

Uses of Seaborn

Distribution Plots
Pie Chart & Bar Chart
Scatter Plots
Pair Plots
Heat maps

6. TensorFlow

TensorFlow is an open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks.

Uses of Tensorflow

Voice/Sound Recognition
Classification, Perception
Understanding
Discovering
Prediction and Creation.

7. Scikit Learn

Scikit-learn is a free software machine learning and data analysis library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines

Uses of Scikit Learn

Regression and clustering
Model selection
Dimensionality reduction
Ensemble methods
Feature extractionFeature selection
Parameter Tuning
Manifold Learning
Supervised Models

8. PyTorch

PyTorch is an source machine learning framework that accelerates the path from research prototyping to production deployment. it is used for applications such as computer vision and natural language processing, primarily developed by Facebook's AI Research lab.

Uses of PyTorch

Distributed Training
Robust Ecosystem
Cloud support
Production Ready

9. Keras

Keras is an open-source software library that provides a Python interface for artificial neural networks. Keras acts as an interface for the TensorFlow library.
It is API designed for human beings, not machines. Keras follows best practices for reducing cognitive load

Uses of Keras

High-level neural networks AP
Multi-GPU & distributed training
Activation, and cost functions
TensorFlow Cloud Support

10. PyCaret

PyCaret is an open source, low-code machine learning library in Python that allows you to go from preparing your data to deploying your model within minutes in your choice of notebook environment.

Uses of PyCaret

Building ensemble models
Encoding categorical data,
Feature engineering
Hyperparameter tuning
Model deployment.

Connect Me on Github! Twitter Linkedin

Happy coding😍❤

Hack This Fall 2.0 |Innovate For Good

Rishabh Rathore — Wed, 29 Sep 2021 20:04:57 +0000

The Hack This Fall Hackathon is a 48 hour virtual hackathon where we aim to promote hackers, nurture their new ideas, and support them in solving shared problems.We also aim to involve more beginner hackers and support everyone to solve the shared problems of our society.

We are focussing on creating more learning opportunities along with building and solving. We will talk about various technologies, create awareness, encourage others, hack to contribute, and participate in many more exciting events & sessions.

Where - ✨Virtual Event✨
When - 📅 22-24 October 2021🎁

Learn More

Till Now We Has Crossed 1700+ registrations🎊🎊🎉

Additionally, we have HTF Connects, Live You Sessions, and many other awesome things.

For More Update Join Our Discord Server

Get Your Digital Swag

Here are some pictures of previous HTF Connects!!🎉🎉😎

What is Version Control System?

Rishabh Rathore — Wed, 25 Aug 2021 18:08:43 +0000

A version control system(VCS) is a tool or software that helps to manage different versions of the source code. A source code manager is another name for a version control system.

In other words Version control is a system that carries all the records of file changes or sets of files with respect to time so that we can easily switch to previous versions later.

What is Git?

Git is a type of version control system (VCS) that helps to track the file changes in an easy manner. Git is a free and open-source distributed version control system that has a simple UI design that everyone can understand easily. With the help of Git, we can track small to very large projects with speed and efficiency.

A repository is a Collection of the Source code or files of the project work, Repositories can exist either in the local environment or in the form of a remote copy on another computer. A repository is made up of commits.
Working Directory is the source code or files that you see in your computer's file system. When you open your project files upon a code editor, you're working with files in the Working Directory.
Staging Area: A Stage all Changes in the Current directory that stores information about Changes that you commit. You can think of the staging area as a prep table where Git will take the next commit.
Branch is a new line of development is created that diverges from the main line of development. This alternative line of development can continue without altering the main line.

How To Setup Git?

To download Git

Go to Git-scm.com
Download Git Acc. to the Operating system
install Git choosing all of the default option

Open GitBash

First Time Git Configuration

# sets up Git with your name
git config --global user.name "<Your-Full-Name>"

# sets up Git with your email
git config --global user.email "<your-email-address>"

Create a new project.Open git bash in project directory then initialize project

git init

The git init command creates a new Git repository or initialize a new, empty repository.

touch - used to Create a new file
ls - used to list files and directories
mkdir - used to create a new directory
cd - used to change directories
rm - used to remove files and directories

Create A Web Project

create an index.html file

touch index.html

create a javaScript file

touch main.html

create a style.css file

touch style.css

git status

git status command displays the state of the working directory and the staging area.

git add .

git add command adds a file to the Git staging area.

git commit - m "initial commit"

git commit -m Used to Save Your changes in local repository.