Data Archive
Search
Search
Dark mode
Light mode
Explorer
pages
Data Archive
DE_Tools
ML_Tools
Quotes
Research Questions
Reviews
standardised
1-on-1 Template
1-to-1's with a Line Manager
AB testing
Accessing Gen AI generated content
Accuracy
ACID Transaction
Activation atlases
Activation Function
Active Learning
Ada boosting
Adam Optimizer
Adaptive Learning Rates
Adding a database to PostgreSQL
Addressing Multicollinearity
Addressing_Multicollinearity.py
Adjusted R squared
Agent Exploration
Agent-based modelling
Agentic Solutions
Aggregation
AI Agents Memory
AI Engineer
AI governance
Algorithms
Altair
altair versus seaborn
Alternatives to Batch Processing
Amazon S3
Analytics Engineer
Anomaly Detection
Anomaly Detection in Time Series
Anomaly Detection with Clustering
Anomaly Detection with Statistical Methods
ANOVA
Apache Airflow
Apache Iceberg
Apache Kafka
Apache Spark
API
API Driven Microservices
ARIMA
Asking questions
Assumption of Normality
Attack mitigation
Attack types
Attention Is All You Need
Attention mechanism
AUC
Automated Feature Creation
AWS Lambda
Azure
Backpropagation
Bag of words
Bag_of_Words.py
Bagging
Bandit example output
Bandit_Example_Fixed.py
Bash
bat
Batch Normalisation
Batch Processing
Batch vs PowerShell scripts
Bellman Equations
Benefits of Data Transformation
Bernoulli
BERT
BERT Pretraining of Deep Bidirectional Transformers for Language Understanding
BERTScore
Bias and variance
Big Data
big o notation
BigQuery
binary classification
Binder
Boosting
Bootstrap Sampling
Boxplot
business intelligence
Business observability
Business value of anomaly detection
Capability
Casual Inference
CatBoost
Central Limit Theorem
Central Limit Theorem & Small Sample Sizes
Chain of thought
Change Management
ChatGPT
Checksum
Chi-Squared Test
Choosing a Threshold
Choosing the Number of Clusters
CI-CD
Class Separability
Classification
Classification Report
Claude
Click_Implementation.py
Cloud Providers
Cluster Density
Cluster Seperation
Clustering
Clustering_Dashboard.py
Clustermap
Code Diagrams
Columnar Storage
Command line
Command Prompt
Common Table Expression
Communication principles
Communication Techniques
Comparing LLMs
Comparing_Ensembles.py
Components of the database
Computer Science
conceptual data model
Conceptual Model
Concurrency
Confidence Interval
Confusion Matrix
Continuous Delivery - Deployment
Continuous Integration
Convolutional Neural Networks
Correlation
Correlation vs Causation
Cosine Similarity
Cost Function
Cost-Sensitive Analysis
Covariance
Covariance Structures
Covariance vs Correlation
Covering Index
Cron jobs
Cross Entropy
Cross validation
Cross_Entropy_Single.py
Cross_Entropy.py
Crosstab
CRUD
Cryptography
csv module
CUDA
Curse of dimensionality
Cypher
dagster
Dash
Dashboarding
Data AI Education at Work
Data Analysis
Data Analysis Portal
Data Analyst
Data Architect
Data Architecture
Data Assessment
Data Assessment for Predictive Modeling
Data Cleansing
Data Collection
Data Contract
Data Distribution
Data Drift
Data Engineer
Data Engineering
Data Engineering Portal
Data Engineering Tools
data governance
data hierarchy of needs
Data Ingestion
data integration
Data Integrity
Data Lake
Data Lakehouse
Data Leakage
Data Lifecycle Management
data lineage
data literacy
Data Management
Data Mining - CRISP
Data Modelling
Data Observability
Data Orchestration
Data Pipeline
Data Pipeline to Data Products
Data Preparation
Data Principles
data product
data quality
Data Reduction
Data Roles
Data Science
Data Scientist
Data Security
Data Selection
Data Selection in ML
Data Steward
Data storage
Data Streaming
Data Transformation
Data transformation in Data Engineering
Data transformation in Machine Learning
Data Transformation with Pandas
Data Validation
data virtualization
Data Visualisation
Data Warehouse
Database
Database Index
Database Management System (DBMS)
Database schema
Database Storage
Database Techniques
Databricks
Databricks 1
Databricks vs Snowflake
DataOps
Datasets
DBScan
dbt
dbt 1
Debugging
Debugging ipynb
Debugging.py
Decision Tree
Declarative Data Pipeline
Deep Learning
Deep Learning Frameworks
Deep Q-Learning
Demand forecasting
Dendrograms
dependency manager
Design Thinking Questions
Determining Threshold Values
DevOps
Differentation
Digital Transformation
Digital twin
Dimension Table
Dimensional Modelling
Dimensionality Reduction
dimensions
Directed Acyclic Graph (DAG)
Distillation
Distributed Computing
Distribution_Analysis.py
Distributions
Docker
Docker Image
documentation
Documentation & Meetings
Dropout
DS & ML Portal
duckdb
DuckDB in python
DuckDB vs SQLite
Dummy variable trap
EDA
Edge ML
Education and Training
Elastic Net
ElasticSearch
ELT
Embedded Methods
embeddings for OOV words
emergent behavior
Encoding Categorical Variables
Energy
Energy ABM
Energy Storage
Environment Variables
Epoch
Epub
ER Diagrams
Estimator
ETL
ETL 1
ETL Pipeline example
etl vs elt
etlt
Evaluate Embedding Methods
Evaluating Language Models
Evaluating the effectiveness of prompts
Evaluation Metrics
Event Driven
Event Driven Events
Event Driven Microservices
Event-Driven Architecture
Everything
Excel
Excel 1
Excel pivot table
Excel vs Google Sheets
Experiment Plan Template
Exploration vs Exploitation
f-regression
F-statistic
F1 Score
Fabric
fact table
Factor Analysis
Factor_Analysis.py
facts
FAISS
Faker
FastAPI
FastAPI_Example.py
Feature Engineering
Feature Evaluation
Feature Extraction
Feature Importance
Feature Scaling
Feature Selection
Feature Selection vs Feature Importance
Feature Transformations
Feature_Distribution.py
Feed Forward Neural Network
Feedback Template
File Management
Filter method
filter methods
Firebase
Fishbone diagram
Fitting weights and biases of a neural network
Flask
Folder Tree Diagram
Forecasting_AutoArima.py
Forecasting_Baseline.py
Forecasting_Exponential_Smoothing.py
Foreign Key
Forward Propagation
Framework for models
frontend
functional programming
Fuzzywuzzy
garbage collector
Gartner Hype Cycle
Gaussian Distribution
Gaussian Mixture Models
Gaussian Model
gaussian_mixture_model_implementation.py
General Linear Regression
Generative Adversarial Networks
Generative AI
Generative AI From Theory to Practice
Generators in Python
Gini Impurity
Gini Impurity vs Cross Entropy
GIS
Git
Gitlab
gitlab-ci.yml
Global Interpreter Lock
Google Cloud Platform
Google Colab
Google My Maps Data Extraction
Google OR Tools
Google Sheet Pivots Table
Google Sheets
GPT
Gradient Boosting
Gradient Boosting Regressor
Gradient Descent
Gradient descent in linear regression
Gradio
Grain
Grammar method
granularity
Graph Neural Network
Graph Query Language
Graph Theory
Graph Theory Community
GraphRAG
Grep
GridSeachCv
Groupby
Groupby vs Crosstab
Grouped plots
GRU
Guardrails
Hadoop
Handling Different Distributions
Handling Missing Data
Handling_Missing_Data_Basic.ipynb
Handling_Missing_Data.ipynb
Hash
Heap Data Structure
Heap Memory
Heatmap
Heatmaps_Dendrograms.py
heterogeneous features
Hierarchical Clustering
High cross validation accuracy is not directly proportional to performance on unseen test data
Honkit
Hosting
How businesses use Gen AI
How do we evaluate of LLM Outputs
how do you do the data selection
How is reinforcement learning being combined with deep learning
How is schema evolution done in practice with SQL
How LLMs store facts
How to do git commit messages properly
How to normalise a merged table
How to reduce the need for Gen AI responses
How to search within a graph
How to use Sklearn Pipeline
How would you decide between using TF-IDF and Word2Vec for text vectorization
html
Hugging Face
Hyperparameter
Hyperparameter Tuning
Hypothesis testing
Imbalanced Datasets
Imbalanced_Datasets_SMOTE.py
Immutable vs mutable
Impact of multicollinearity on model parameters
imperative
Implementing Database Schema
Imputation Techniques
In NER how would you handle ambiguous entities
in-memory format
incremental synchronization
Indexing in cypher
Industries of interest
Inertia K Means Cost Function
inference
inference versus prediction
information theory
initialization methods
Input is Not Properly Sanitized
Interoperability
interoperable
interpretability
Interpreting logistic regression model parameters
Interquartile Range (IQR) Detection
ipynb
Isolated Forest
Java
Java vs JavaScript
JavaScript
jinja template
Jobs to be done
Johnson–Lindenstrauss lemma
Joining Datasets
Json
Json to SQLite
Junction Tables
Jupyter Book
jupytext
Justfile
K_Means.py
K-means
K-nearest neighbours
Keras
Kernel Density Estimation
Kernelling
Key Components of Attention and Formula
Kmeans vs GMM
KNIME
Knowledge Graph
Knowledge graph vs RAG setup
Knowledge Work
kubernetes
Label encoding
Label encoding vs One-hot encoding
Labelling data
lambda architecture
Langchain
Language Model Output Optimisation
Language Models
Language Models Large (LLMs) vs Small (SLMs)
Lasso
Latency
Latent Dirichlet Allocation
LBFGS
Learning Curve
learning rate
Learning Styles
lemmatization
LightGBM
LightGBM vs XGBoost vs CatBoost
Linear Discriminant Analysis
Linear Regression
Linked List
linkedin learning
LLM
LLM Evaluation Metrics
LLM Memory
Load Balancing
Local Interpretable Model-agnostic Explainations
Local LLM use cases
Local Outlier Factor (LOF)
Log transformation
Logical Model
Logistic Regression
Logistic Regression does not predict probabilities
Logistic regression in sklearn & Gradient Descent
Logistic Regression Statsmodel Summary table
Looker Studio
loss function
Loss versus Cost function
LSTM
Machine Learning
Machine Learning Algorithms
Machine Learning Operations
maintainability
Maintainable Code
Makefile
Manifold learning
Many-to-Many Relationships
map reduce
Markov chain
Markov Decision Processes
master data management
Master Observability Datadog
Mathematical Reasoning in Transformers
Mathematics
Maximum Likelihood Estimation
mean absolute error
Mean Squared Error
mean vs median
melt
Memory
Memory Caching
Merge
Mermaid
Metadata Handling
Methods for Handling Outliers
metric
Microsoft
Microsoft Access
Mini-batch gradient descent
Mixture of Experts
ML Engineer
MNIST
Model Building
Model Cascading
Model Deployment
Model Ensemble
Model Evaluation
Model Evaluation vs Model Optimisation
Model Interpretability
Model Observability
Model Optimisation
Model Parameters
Model Parameters Tuning
Model parameters vs hyperparameters
Model Selection
Model Validation
model-agnostic feature importance
Modern data team
Momentum
Momentum.py
MongoDB
Monolith Architecture
Monte Carlo Simulation
Multi-Agent Reinforcement Learning
Multi-head attention
Multi-level index
Multicollinearity
Multinomial Naive bayes
Multiprocessing
Multiprocessing vs Multithreading
Multithreading
MySql
Naive Bayes
Named Entity Recognition
nbconvert
nbconvert slideshows
neo4j
neomodel
NET
Network Design
Neural network
Neural Network Classification
Neural network in Practice
Neural Scaling Laws
Ngrams
NLP
nltk
Node.JS
non-parametric
Non-parametric tests
Normalisation
Normalisation of data
Normalisation of Text
Normalisation vs Standardisation
Normalised Schema
NoSQL
NotebookLM
npy Files A NumPy Array storage
Numpy
Object Relational Mapper
Odds
Odds vs Probability
OLAP (online analytical processing)
OLTP
One Pager Template
One_hot_encoding.py
One-hot encoding
OOV words
Operational Resilience for Growth and Adaptability
Optimisation function
Optimisation techniques
Optimising a Logistic Regression Model
Optimising Neural Networks
Optuna
Ordinary Least Squares
Orthogonalization
Outliers
Over parameterised models
Overfitting
p values
Page Rank
Pandas
Pandas Dataframe Agent
Pandas join vs merge
Pandas Pivot Table
Pandas Stack
Pandas_Common.py
Pandas_Stack.py
Pandoc
Parametric tests
parametric vs non-parametric models
parametric vs non-parametric tests
Parquet
parsimonious
Part of speech tagging
PCA Explained Variance Ratio
PCA Principal Components
PCA_Analysis.ipynb
PCA_Based_Anomaly_Detection.py
PCA-Based Anomaly Detection
pd.Grouper
pdoc
PDP and ICE
Percentile Detection
Performance Dimensions
Performance Drift
pgAdmin
Physical Model
Pickle
Plotly
pmdarima
Poetry
Polars
Policy
Polynomial Regression
Positional Encoding
PostgreSQL
Postman
PowerBI
Powerquery
PowerShell
Powershell scripts
Powershell versus Command Prompt
Powershell vs Bash
Precision
Precision or Recall
Precision-Recall Curve
Prediction Intervals
Preprocessing
Prevention Is Better Than the Cure
Primary Key
Principal Component Analysis
Probability
Problem Definition
Process Based Parallelism
Processes vs Threads
programming languages
project management
Project Management Portal
Prompt engineering
prompt retrievers
Prompts
Proportion Test
Publish and Subscribe
Pull Request Template
push-down
PyCaret
Pycaret_Anomaly.ipynb
Pycaret_Example.py
Pydantic
Pydantic_More.py
Pydantic.py
PyGraphviz
PyOD
Pyright
Pyright vs Pydantic
PySpark
Pytest
Python
Python Click
PyTorch
Pytorch vs Tensorflow
Q-Learning
Q-Q Plot
Quartz
Query Optimisation
Querying
QuickSort
R
R squared
R-squared metric not always a good indicator of model performance in regression
Race Conditions
RACI
RAG
Random Access Memory
Random Forest Regression
Random Forests
React
Reasoning tokens
Recall
Recommender systems
Recurrent Neural Networks
Recursive Algorithm
Registering a Scheduled Task
Regression
Regression metrics
Regression_Logistic_Metrics.ipynb
Regularisation
Regularisation of Tree based models
Regularisation.py
Reinforcement learning
Relating Tables Together
Relational Database
Relationships in memory
Relu
Reporting
REST API
Return of Experience Form
Reveal.js
reverse etl
Reward Function
Ridge
ROC (Receiver Operating Characteristic)
ROC_Curve.py
rollup
Root Mean Squared Error
Row-based Storage
Sampling
Sarsa
Scala
Scalability
Scaling Agentic Systems
Scaling Data Science Capability
Scaling Server
Scatter Plots
schema evolution
Scientific Method
Scikit-Learn
Scipy
Seaborn
search
Security mitigation
Security Researcher
Security Vulnerabilities
Self Attention
Self attention vs multi-head attention
Self-Attention
semantic layer
Semantic Relationships
Semantic search
semi-structured data
Sentence Similarity
Sentence Transformer Workflow
Sentence Transformers
shapefile
SHapley Additive exPlanations
Sharepoint
Silhouette Analysis
Similarity Search
Single source of truth
sklearn datasets
Sklearn Pipiline
Slowly Changing Dimension
Small Language Models
Smart Grids
SMOTE (Synthetic Minority Over-sampling Technique)
SMSS
Snowflake
Snowflake Schema
Snowflake vs Hadoop
Soft Deletion
Software Design Patterns
Software Development Life Cycle
Software Development Portal
spaCy
SparseCategorialCrossentropy or CategoricalCrossEntropy
Spearman vs Pearson Correlation
Specificity
Spreadsheets vs Databases
SQL
SQL Groupby
SQL Injection
SQL Joins
SQL vs NoSQL
SQL Window functions
SQLAlchemy
SQLAlchemy vs. sqlite3
SQLite
SQLite Studio
stack memory
Stacking
Standard deviation
Standardisation
Star Schema
Statistical Assumptions
Statistical Tests
Statistical theorems
Statistics
Stemming
Stochastic Gradient Descent
storage layer object store
Stored Procedures
Strategy for choosing Data Sources
Streamlit
Strongly vs Weakly typed language
structured data
Structuring and organizing data
Summarisation
Supervised Learning
Support Vector Classifier
Support Vector Machines
Support Vector Regression
SVM_Example.py
Symbolic computation
Sympy
syntactic relationships
t-SNE
T-test
Tableau
Technical Debt
Technical Design Doc Template
Telecommunications
Tensorflow
Terminal commands
Test Loss When Evaluating Models
Testing
Testing_Pytest.py
Testing_unittest.py
Text2Cypher
TF-IDF
TF-IDF Implementation
Thinking Systems
Time Series
Time Series Forecasting
Time Series Identify Trends and Patterns
Tokenisation
TOML
tool.bandit
tool.ruff
tool.uv
topic modeling
Train-Dev-Test Sets
Transaction
Transfer Learning
transfer_learning.py
Transformed Target Regressor
Transformer
Transformers vs RNNs
TS_Anomaly_Detection.py
Turning a flat file into a database
Type I Error (False Positive)
Type II Error (False Negative)
Types of Computational Bugs
Types of Database Schema
Types of Neural Networks
TypeScript
Typical Output Formats in Neural Networks
Ubuntu
UMAP
UML
unittest
univariate vs multivariate
Unix
unstructured data
Unsupervised learning
Untitled
Untitled 1
Usability
Use Cases for a Simple Neural Network Like
Use of RNNs in energy sector
Vacuum
vanishing and exploding gradients problem
Variability in linear models
variance
Vector Database
Vector Embedding
Vector_Embedding.py
Vectorisation
Vectorized Engine
Vercel
View Use Case
Views
Violin plot
Virtual environments
WCSS and elbow method
Weak Learners
Web Feature Server (WFS)
Web Map Tile Service (WMTS)
When and why not to us regularisation
Why does increasing the number of models in a ensemble not necessarily improve the accuracy
Why does the Adam Optimizer converge
Why is named entity recognition (NER) a challenging task
Why JSON is Better than Pickle for Untrusted Data
Why Removing Outliers May Improve Regression but Harm Classification
Why standardise features
Why Type 1 and Type 2 matter
Why use ER diagrams
Wikipedia_API.py
Windows
Windows Scheduled Tasks
Windows Subsystem for Linux
Word2vec
Word2Vec.py
WordNet
Working with SMEs
Wrapper Methods
Xaiver
XGBoost
yaml
Z-Normalisation
Z-Score
Z-Scores vs Prediction Intervals
Z-Test
Plotly
Python visualisation tool.