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Add machine learning roadmap
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---
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jsonUrl: '/jsons/roadmaps/ai-data-scientist.json'
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pdfUrl: '/pdfs/roadmaps/ai-data-scientist.pdf'
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order: 5
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order: 4.5
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renderer: 'editor'
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briefTitle: 'AI and Data Scientist'
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briefDescription: 'Step by step guide to becoming an AI and Data Scientist in 2025'
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title: 'AI Engineer'
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description: 'Step by step guide to becoming an AI Engineer in 2025'
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hasTopics: true
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isNew: true
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isNew: false
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dimensions:
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width: 968
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height: 3200
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---
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pdfUrl: '/pdfs/roadmaps/android.pdf'
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renderer: 'editor'
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order: 5
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order: 4.7
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briefTitle: 'Android'
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briefDescription: 'Step by step guide to becoming an Android Developer in 2025'
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title: 'Android Developer'
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briefDescription: 'Learn to deploy your applications on Cloudflare'
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title: 'Cloudflare'
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description: 'Learn to deploy your applications on Cloudflare'
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isNew: true
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isNew: false
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hasTopics: true
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renderer: editor
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dimensions:
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---
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jsonUrl: '/jsons/roadmaps/data-engineer.json'
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pdfUrl: '/pdfs/roadmaps/data-engineer.pdf'
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order: 4
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order: 4.6
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renderer: "editor"
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briefTitle: 'Data Engineer'
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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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# CSV
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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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# GRU
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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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# IoT
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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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