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Machine & Deep Learning Compendium
  • The Machine & Deep Learning Compendium
    • Thanks Page
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  • Types Of Machine Learning
    • Overview
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    • Active Learning
    • Online Learning
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  • Foundation Knowledge
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    • Calculus
    • Probability & Statistics
    • Probability
    • Hypothesis Testing
    • Feature Types
    • Multi Label Classification
    • Distribution
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    • Normalization & Scaling
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    • Information Theory
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    • Multi CPU Processing
    • Benchmarking
  • Validation & Evaluation
    • Features
    • Evaluation Metrics
    • Datasets
    • Dataset Confidence
    • Hyper Parameter Optimization
    • Training Strategies
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    • Datasets Reliability & Correctness
    • Data & Model Tests
    • Fairness, Accountability, and Transparency
    • Interpretable & Explainable AI (XAI)
    • Federated Learning
  • Machine Learning
    • Algorithms 101
    • Meta Learning (AutoML)
    • Probabilistic, Regression
    • Data Mining
    • Process Mining
    • Label Algorithms
    • Clustering Algorithms
    • Anomaly Detection
    • Decision Trees
    • Active Learning Algorithms
    • Linear Separator Algorithms
    • Regression
    • Ensembles
    • Reinforcement Learning
    • Incremental Learning
    • Dimensionality Reduction Methods
    • Genetic Algorithms & Genetic Programming
    • Learning Classifier Systems
    • Recommender Systems
    • Timeseries
    • Fourier Transform
    • Digital Signal Processing (DSP)
    • Propensity Score Matching
    • Diffusion models
  • Classical Graph Models
    • Graph Theory
    • Social Network Analysis
  • Deep Learning
    • Deep Neural Nets Basics
    • Deep Neural Frameworks
    • Embedding
    • Deep Learning Models
    • Deep Network Optimization
    • Attention
    • Deep Neural Machine Vision
    • Deep Neural Tabular
    • Deep Neural Time Series
  • Audio
    • Basics
    • Terminology
    • Feature Engineering
    • Deep Neural Audio
    • Algorithms
  • Natural Language Processing
    • A Reality Check
    • NLP Tools
    • Foundation NLP
    • Name Matching
    • String Matching
    • TF-IDF
    • Language Detection Identification Generation (NLD, NLI, NLG)
    • Topics Modeling
    • Named Entity Recognition (NER)
    • SEARCH
    • Neural NLP
    • Tokenization
    • Decoding Algorithms For NLP
    • Multi Language
    • Augmentation
    • Knowledge Graphs
    • Annotation & Disagreement
    • Sentiment Analysis
    • Question Answering
    • Summarization
    • Chat Bots
    • Conversation
  • Generative AI
    • Methods
    • Gen AI Industry
    • Speech
    • Prompt
    • Fairness, Accountability, and Transparency In Prompts
    • Large Language Models (LLMs)
    • Vision
    • GPT
    • Mix N Match
    • Diffusion Models
    • GenAI Applications
    • Agents
    • RAG
    • Chat UI/UX
  • Experimental Design
    • Design Of Experiments
    • DOE Tools
    • A/B Testing
    • Multi Armed Bandits
    • Contextual Bandits
    • Factorial Design
  • Business Domains
    • Follow the regularized leader
    • Growth
    • Root Cause Effects (RCE/RCA)
    • Log Parsing / Templatization
    • Fraud Detection
    • Life Time Value (LTV)
    • Survival Analysis
    • Propaganda Detection
    • NYC TAXI
    • Drug Discovery
    • Intent Recognition
    • Churn Prediction
    • Electronic Network Frequency Analysis
    • Marketing
  • Product Management
    • Expanding Your Data Science Skills
    • Product Vision & Strategy
    • Product / Program Managers
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    • Product Tools
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User Experience Design (UX)

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  1. is a collection of best practices that designers can consider when building user interfaces.

  2. - One-stop resource for everything related to user experience, a medium publication

  3. - blog posts and best practices about UX, XD, UI

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  1. (really good) Growth design

Laws of UX
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