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Reading list

6 Steps of Machine learning Lifecycle Introduction to Predictive Modeling
Introduction to Exploratory Data Analysis & Data Insights Descriptive Statistics Inferential Statistics How to Understand Population Distributions?
Reading Data Files into Python Different Variable Datatypes
Probability for Data Science Basic Concepts of Probability Axioms of Probability Conditional Probability
Central Tendencies for Continuous Variables Spread of Data KDE plots for Continuous Variable Overview of Distribution for Continuous variables Normal Distribution Skewed Distribution Skeweness and Kurtosis Distribution for Continuous Variable
Central Tendencies for Categorical Variables Understanding Discrete Distributions Performing EDA on Categorical Variables
Dealing with Missing Values Understanding Outliers Identifying Outliers in Data Outlier Detection in Python Outliers Detection Using IQR, Z-score, LOF and DBSCAN
Sample and Population Central Limit Theorem Confidence Interval and Margin of Error
Bivariate Analysis Introduction
Covariance Pearson Correlation Spearman's Correlation & Kendall's Tau Correlation versus Causation Tabular and Graphical methods for Bivariate Analysis Performing Bivariate Analysis on Continuous-Continuous Variables
Tabular and Graphical methods for Continuous-Categorical Variables Introduction to Hypothesis Testing P-value Two sample Z-test T-test T-test vs Z-test Performing Bivariate Analysis on Continuous-Catagorical variables
Chi-Squares Test Bivariate Analysis on Categorical Categorical Variables
Multivariate Analysis A Comprehensive Guide to Data Exploration The Data Science behind IPL
Supervised Learning vs Unsupervised Learning Reinforcement Learning Generative and Descriminative Models Parametric and Non Parametric model
Machine Learning Pipeline Preparing Dataset Build a Benchmark Model: Regression Build a Benchmark Model: Classification
Evaluation Metrics for Machine Learning Everyone should know Confusion Matrix Accuracy Precision and Recall AUC-ROC Log Loss R2 and Adjusted R2
Dealing with Missing Values Replacing Missing Values Imputing Missing Values in Data Working with Categorical Variables Working with Outliers Preprocessing Data for Model Building
Understanding Cost Function Understanding Gradient Descent Math Behind Gradient Descent Assumptions of Linear Regression Implement Linear Regression from Scratch Train Linear Regression in Python Implementing Linear Regression in R Diagnosing Residual Plots in Linear Regression Models Generalized Linear Models Introduction to Logistic Regression Odds Ratio Implementing Logistic Regression from Scratch Introduction to Scikit-learn in Python Train Logistic Regression in python Multiclass using Logistic Regression How to use Multinomial and Ordinal Logistic Regression in R ? Challenges with Linear Regression Introduction to Regularisation Implementing Regularisation Ridge Regression Lasso Regression
Introduction to K Nearest Neighbours Determining the Right Value of K in KNN Implement KNN from Scratch Implement KNN in Python
Bias Variance Tradeoff Introduction to Overfitting and Underfitting Visualizing Overfitting and Underfitting Selecting the Right Model What is Validation? Hold-Out Validation Understanding K Fold Cross Validation
Introduction to Feature Selection Feature Selection Algorithms Missing Value Ratio Low Variance Filter High Correlation Filter Backward Feature Elimination Forward Feature Selection Implement Feature Selection in Python Implement Feature Selection in R
Introduction to Decision Tree Purity in Decision Tree Terminologies Related to Decision Tree How to Select Best Split Point in Decision Tree? Chi-Squares Information Gain Reduction in Variance Optimizing Performance of Decision Tree Train Decision Tree using Scikit Learn Pruning of Decision Trees
Introduction to Feature Engineering Feature Transformation Feature Scaling Feature Engineering Frequency Encoding Automated Feature Engineering: Feature Tools
Understanding how to solve Multiclass and Multilabled Classification Problem Evaluation Metrics: Multi Class Classification
Introduction to Ensemble Techniques Basic Ensemble Techniques Implementing Basic Ensemble Techniques Finding Optimal Weights of Ensemble Learner using Neural Network Why Ensemble Models Work well?
Introduction to Stacking Implementing Stacking Variants of Stacking Implementing Variants of Stacking Introduction to Blending Bootstrap Sampling Introduction to Random Sampling Hyper-parameters of Random Forest Implementing Random Forest Out-of-Bag (OOB) Score in the Random Forest IPL Team Win Prediction Project Using Machine Learning Introduction to Boosting Gradient Boosting Algorithm Math behind GBM Implementing GBM in python Regularized Greedy Forests Extreme Gradient Boosting Implementing XGBM in python Tuning Hyperparameters of XGBoost in Python Implement XGBM in R/H2O Adaptive Boosting Implementing Adaptive Boosing LightGBM Implementing LightGBM in Python Catboost Implementing Catboost in Python
Different Hyperparameter Tuning methods Implementing Different Hyperparameter Tuning methods GridsearchCV RandomizedsearchCV Bayesian Optimization for Hyperparameter Tuning Hyperopt
Understanding SVM Algorithm SVM Kernels In-depth Intuition and Practical Implementation SVM Kernel Tricks Kernels and Hyperparameters in SVM Implementing SVM from Scratch in Python and R
Introduction to Principal Component Analysis Steps to Perform Principal Compound Analysis Computation of Covariance Matrix Finding Eigenvectors and Eigenvalues Implementing PCA in python Visualizing PCA A Brief Introduction to Linear Discriminant Analysis Introduction to Factor Analysis
Introduction to Clustering Applications of Clustering Evaluation Metrics for Clustering Understanding K-Means Implementation of K-Means in Python Implementation of K-Means in R Choosing Right Value for K Profiling Market Segments using K-Means Clustering Hierarchical Clustering Implementation of Hierarchial Clustering DBSCAN Defining Similarity between clusters Build Better and Accurate Clusters with Gaussian Mixture Models
Understand Basics of Recommendation Engine with Case Study
8 Ways to Improve Accuracy of Machine Learning Models
Introduction to Dask Working with CuML
Introduction to Machine Learning Interpretability Framework and Interpretable Models model Agnostic Methods for Interpretability Implementing Interpretable Model Understanding SHAP Out-of-Core ML Introduction to Interpretable Machine Learning Models Model Agnostic Methods for Interpretability Game Theory & Shapley Values
Introduction to AutoML Implementation of MLBox Introduction to PyCaret TPOT Auto-Sklearn EvalML
Pickle and Joblib Introduction to Model Deployment
Deploying Machine Learning Model using Streamlit Deploying ML Models in Docker Deploy Using Streamlit Deploy on Heroku Deploy Using Netlify Introduction to Amazon Sagemaker Setting up Amazon SageMaker Using SageMaker Endpoint to Generate Inference Deploy on Microsoft Azure Cloud Introduction to Flask for Model Deploying ML model using Flask
Model Deployment in Android Model Deployment in Iphone

How to Install Git?

JanviKumari01
JanviKumari01 22 Aug, 2024
5 min read

Introduction

Git is an essential tool for developers, streamlining project collaboration and version control. Getting Git up and running on your machine is straightforward, whether you’re on Linux, macOS, or Windows. This guide will walk you through each step, ensuring you can efficiently manage your projects. Ready to take control of your code? Let’s get started with installing Git!

Overview

  • Learn why Git is essential for developers and how it simplifies collaboration and version control.
  • Get step-by-step instructions on how to install Git on Linux, macOS, and Windows easily.
  • Understand how Git empowers efficient project management through robust backup and recovery.
  • Discover how Git integration boosts productivity with automation and open-source contributions.
  • Prepare for a successful coding career by mastering Git, the industry-standard version control tool.

Table of contents

Why Will You Need Git?

You’ll need Git because it’s the backbone of modern software development. Here’s why:

  1. Version Control: Git allows you to track changes in your code over time. This means you can revert to previous versions if something goes wrong, compare changes, and even understand who made specific changes and why.
  2. Collaboration: Git enables multiple developers to work on the same project simultaneously without stepping on each other’s toes. By using branches, each team member can work independently on different features or fixes and then seamlessly merge their work together.
  3. Backup and Recovery: With Git, your entire project history is stored, ensuring you can recover lost work or roll back to a stable state if needed. It’s like having an insurance policy for your code.
  4. Open Source Projects: Many open-source projects use Git. By understanding and using Git, you can contribute to these projects, learn from others, and even get your work recognized in the broader developer community.
  5. Efficiency and Automation: Git integrates with various tools and platforms, allowing for automated testing, continuous integration, and deployment. This speeds up your workflow and reduces the chances of human error.
  6. Industry Standard: Most tech companies and development teams use Git. Knowing how to use it is often a requirement for development roles, making it a critical skill for your career.

Now, let’s install Git:

Checking for Git Installation

Before installing Git, checking if it’s already installed on your machine is a good idea.

  1. Open your terminal or command prompt:
    • macOS: Use the built-in Terminal application.
    • Windows: Open Command Prompt or Git Bash.
    • Linux: Use your preferred terminal application.
  2. Check Git version: Type the following command and press Enter:
git version

If Git is installed, you’ll see the version number. If not, you’ll need to install it.

Installing Git on Windows

Windows users have a couple of options for installing Git.

Option 1 for Installation

 Using the Git for Windows Installer:

  1. Download the installer: Go to the Git for Windows website and download the latest version.
  2. Run the installer: Double-click the downloaded file and follow the setup wizard instructions.
  3. Select components: During the installation, you’ll have options like adjusting your PATH environment, choosing the default editor, and more. Most users can go with the default settings.
  4. Complete installation: Finish the setup, then open Command Prompt or Git Bash.

       5. Verify installation: Run the command:

git version

This will confirm that Git is installed and ready to use.

Option 2 for Installation

 Installing Git via GitHub Desktop:

  1. Download GitHub Desktop: Head over to the GitHub Desktop website and download the application.
  2. Install and run: Install GitHub Desktop, which includes Git. This option provides a GUI (Graphical User Interface) alongside the command-line tool.
  3. Verify installation: After installation, use the Git version command to check the Git version in Command Prompt or Git Bash.

Installing Git on macOS

macOS users often find Git pre-installed on their systems. However, if it’s unavailable or you need the latest version, follow these methods.

Option 1 for Installation

 Installing Git via Homebrew

  1. Install Homebrew: If you don’t have Homebrew installed, first install it by running the following command in Terminal:
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
  1. Install Git: Once Homebrew is installed, install Git by typing:
brew install git
  1. Verify installation: Confirm Git’s installation with:
git version

Option 2: Using the macOS Git Installer

  1. Download the installer: Visit the Git-scm website and download the latest Git installer for macOS.
  2. Run the installer: Open the downloaded file and follow the installation instructions.
  3. Verify installation: Use the git version command in Terminal to ensure Git is installed.

Installing Git on Linux

Linux users can install Git easily using their distribution’s package manager.

Option 1 for Installation

Installing Git on Debian/Ubuntu

  1. Update package index:  Open your terminal and run:
sudo apt-get update
  1. Install Git:

Install Git using:

sudo apt-get install git-all
  1. Verify installation: Check the installation by running:
git version

Option 2 Installing Git on Fedora

  1. Install Git: Open your terminal and run:
sudo dnf install git-all
  1. Verify installation: Confirm Git’s installation by typing:
git version

Also read: New to Git and GitHub? This Essential Beginners Guide is for you

Conclusion

Installing Git is simple on Linux, macOS, and Windows. Setting up Git on your computer is the first step to effective version control and collaboration, regardless of your expertise level. If you follow the instructions specific to your operating system, you can use Git quickly.

Frequently Asked Questions

Q1.  What are the basic Git commands I should learn after installation?

Ans. After installing Git, familiarize yourself with basic commands such as:
1. Git init: Initialize a new Git repository.
2. Git clone: Clone an existing repository.
3. Git add: Stage changes for commit.
4. Git commit: Commit staged changes.
5. Git push: Push commits to a remote repository.
6. Git pull: Pull updates from a remote repository.

Q2. Can I work with Git using Visual Studio Code?

Ans. Yes, Visual Studio Code has excellent Git integration. You can manage your repositories, commit changes, and even handle pull requests within the editor. The GitHub Pull Requests and Issues extension enhances this experience, especially if you work with GitHub-hosted repositories.

Q3. How do I handle multiple versions of Git on the same system?

Ans. Managing multiple versions of Git can be tricky but is often necessary in complex environments:
1. Windows: You can install Git in different directories and manually adjust your system PATH to point to the version you want to use.
2. macOS/Linux: Use version managers like Homebrew or manually manage symlinks to switch between versions.

Q4. What are the common issues when installing Git, and how do I resolve them?

Ans. Some common installation issues include:
1. PATH not set correctly: Ensure the Git binary path is added to your system’s PATH environment variable.
2. Permission errors: Run the installer as an administrator or use sudo on macOS/Linux.
3. Conflicts with other software: Ensure no other programs use the same resources or paths as Git.

Q5. Is there a way to customize my Git installation for my workflow?

Ans. Yes, during installation, especially on Windows, you can choose custom options like setting your preferred text editor, choosing between different credential helpers, and deciding how Git integrates with your terminal. Post-installation, you can customize Git by editing your .gitconfig file to set aliases, configure diff tools, and more.

Git Bashgit on linuxGit on MacOSGithubinstall gittool for developers
JanviKumari01
JanviKumari01 22 Aug, 2024

Hi I am Janvi Kumari currently a Data Science Intern at Analytics Vidhya, passionate about leveraging data for insights and innovation. Curious, driven, and eager to learn. If you'd like to connect, feel free to reach out to me on LinkedIn

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