Add machine learning roadmap

This commit is contained in:
Kamran Ahmed
2025-08-19 17:30:26 +01:00
parent fc260ec3f0
commit bfe340508c
160 changed files with 6584 additions and 5 deletions

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---
jsonUrl: '/jsons/roadmaps/ai-data-scientist.json'
pdfUrl: '/pdfs/roadmaps/ai-data-scientist.pdf'
order: 5
order: 4.5
renderer: 'editor'
briefTitle: 'AI and Data Scientist'
briefDescription: 'Step by step guide to becoming an AI and Data Scientist in 2025'

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@@ -8,7 +8,7 @@ briefDescription: 'Step by step guide to becoming an AI Engineer in 2025'
title: 'AI Engineer'
description: 'Step by step guide to becoming an AI Engineer in 2025'
hasTopics: true
isNew: true
isNew: false
dimensions:
width: 968
height: 3200

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---
pdfUrl: '/pdfs/roadmaps/android.pdf'
renderer: 'editor'
order: 5
order: 4.7
briefTitle: 'Android'
briefDescription: 'Step by step guide to becoming an Android Developer in 2025'
title: 'Android Developer'

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@@ -6,7 +6,7 @@ briefTitle: 'Cloudflare'
briefDescription: 'Learn to deploy your applications on Cloudflare'
title: 'Cloudflare'
description: 'Learn to deploy your applications on Cloudflare'
isNew: true
isNew: false
hasTopics: true
renderer: editor
dimensions:

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---
jsonUrl: '/jsons/roadmaps/data-engineer.json'
pdfUrl: '/pdfs/roadmaps/data-engineer.pdf'
order: 4
order: 4.6
renderer: "editor"
briefTitle: 'Data Engineer'
briefDescription: 'Step by step guide to becoming an Data Engineer in 2025'

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# Accuracy

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# Activation Functions

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# Actor-Critic Methods

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# APIs

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# Applications of CNNs

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# Attention Mechanisms

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# Attention Models

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# Autoencoders

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# Autoencoders

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# Back Propagation

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# Basic concepts

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# Basic Syntax

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# Basics of Probability

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# Bayes Theorem

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# Calculus

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# Chain rule of derivation

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# Classification

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# Clustering

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# Conditionals

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# Confusion Matrix

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# Convolution

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# Convolutional Neural Network

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# Data Cleaning

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# Data Formats

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# Data Loading

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# Data Preparation

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# Data Sources

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# Data Structures

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# Databases (SQL, No-SQL)

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# Decision Trees, Random Forest

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# Deep Learning Architectures

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# Deep Learning Libraries

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# Deep-Q Networks

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# Derivatives, Partial Derivatives

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# Descriptive Statistics

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# Determinants, inverse of Matrix

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# Dimensionality Reduction

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# Dimensionality Reduction

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# Discrete Mathematics

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# Eigenvalues, Diagonalization

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# ElasticNet Regularization

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# Embeddings

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# Essential libraries

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# Excel

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# Exceptions

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# Exclusive

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# Explainable AI

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# F1-Score

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# Feature Engineering

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# Feature Scaling & Normalization

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# Feature Selection

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# Forward propagation

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# Functions, Builtin Functions

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# Generative Adversarial Networks

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# Gradient Boosting Machines

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# Gradient, Jacobian, Hessian

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# Graphs & Charts

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# Hierarchical

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# Image & Video Recognition

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# Image Classification

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# Image Segmentation

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# Inferential Statistics

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# Internet

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# Introduction

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# JSON

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# K-Fold Cross Validation

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# K-Nearest Neighbors (KNN)

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# Keras

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# Lasso

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# Lemmatization

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# Linear Algebra

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# Linear Algebra

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# Linear Regression

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# Log Loss

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# Logistic Regression

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# LOOCV

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# Loops

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# Loss Functions

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# LSMT

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# Matplotlib

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# Matrix & Matrix Operations

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# Metrics to Evaluate

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# ML Engineer vs AI Engineer

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# Mobile Apps

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# Model Selection

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# Multi-head Attention

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# Natural Language Processing

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# Neural Network (NN) Basics

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# Numpy

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# Object Oriented Programming

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