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DuckDB in python
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etlt
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Event Driven Events
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Everything
Excel
Excel vs Google Sheets
Explain different gradient descent algorithms, their advantages, and limitations.
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fact table
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Factor_Analysis.py
facts
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FastAPI_Example.py
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gaussian_mixture_model_implementation.py
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Gini Impurity vs Cross Entropy
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GraphRAG The Marriage of Knowledge Graphs and RAG
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Groupby vs Crosstab
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Handling_Missing_Data_Basic.ipynb
Handling_Missing_Data.ipynb
Handwritten Digit Classification
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Heatmaps_Dendrograms.py
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High cross validation accuracy is not directly proportional to performance on unseen test data
Honkit
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how do you do the data selection
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How is schema evolution done in practice with SQL
How LLMs store facts
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How would you decide between using TF-IDF and Word2Vec for text vectorization
Hugging Face
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Imbalanced_Datasets_SMOTE.py
Immutable vs mutable
Impact of multicollinearity on model parameters
Implementing Database Schema
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In NER how would you handle ambiguous entities
incremental synchronization
Indexing in cypher
Industries of interest
Inertia K Means Cost Function
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inference versus prediction
information theory
initialization methods
Input is Not Properly Sanitized
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interoperable
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Interpreting logistic regression model parameters
Interquartile Range (IQR) Detection
ipynb
Isolation Forest and Its Use in Anomaly Detection
Java vs JavaScript
JavaScript
Jobs to be done
Johnson–Lindenstrauss lemma
Joining Datasets
Json
Json to SQLite
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Junction Tables
jupytext
Justfile
K_Means.py
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K-nearest neighbours
Keras
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Kmeans vs GMM
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lemmatization
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Microsoft Access
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Mixture of Experts
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MNIST
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Momentum.py
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Multiprocessing vs Multithreading
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MySql
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nbconvert
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Ngrams
nltk
Node.JS
non-parametric
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Normalisation of Text
Normalisation vs Standardisation
NoSQL
NotebookLM
npy Files A NumPy Array storage
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Object Relational Mapper
Odds
Odds vs Probability
OLAP
OLTP
oltp (online transactional processing)
One Pager Template
One_hot_encoding.py
One-hot encoding
OOV words
Operational Resilience for Growth and Adaptability
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Optimisation techniques
Optimising a Logistic Regression Model
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Optuna
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Outliers
Over parameterised models
Overfitting in Machine Learning
p values
Page Rank
Pandas
Pandas Dataframe Agent
Pandas join vs merge
Pandas Pivot Table
Pandas Stack
Pandas_Common.py
Pandas_Stack.py
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 in Machine Learning
Physical Model
Pickle
Plotly
pmdarima
Poetry
Positional Encoding
PostgreSQL
Postman
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Powershell versus cmd
Powershell vs Bash
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Precision or Recall
Precision-Recall Curve
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Prevention Is Better Than the Cure
Primary Key
Principal Component Analysis
Probability
Probability in other fields
Problem Definition
Process Based Parallelism
Processes vs Threads
programming languages
Project Management Portal
Prompt engineering
Prompt Extracting information from blog posts
prompt retrievers
Prompting
Proportion Test
Publish and Subscribe
Pull Request Template
PyCaret
Pycaret_Anomaly.ipynb
Pycaret_Example.py
Pydantic
Pydantic_More.py
Pydantic.py
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PyOD
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Pyright vs Pydantic
PySpark
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Python Click
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Pytorch vs Tensorflow
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Q-Q Plot
Quartz
QUERY GSheets
Query Optimisation
Querying
QuickSort
R
R squared
R-squared metric not always a good indicator of model performance in regression
Race Conditions
RAG
Random Forest Regression
Random Forests
React
Reasoning tokens
Recall
Recommender systems
Recurrent Neural Networks
Recursive Algorithm
Registering a Scheduled Task
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Regression metrics
Regression_Logistic_Metrics.ipynb
Regularisation of Tree based models
Regularisation.py
Regularization in Machine Learning
Reinforcement learning
Relating Tables Together
Relational Database
Relationships in memory
Relu
REST API
retriever
Reward Function
Ridge
ROC (Receiver Operating Characteristic)
ROC_Curve.py
rollup
Row-based Storage
Sarsa
Scala
Scalability
Scaling Agentic Systems
Scaling Data Science Capability
Scaling Server
Scientific Method
Scikit-Learn
Scipy
Seaborn
Security mitigation
Security Researcher
Security Vulnerabilities
semantic layer
Semantic Relationships
Semantic search
Sentence Similarity
Sentence Transformers
shapefile
SHapley Additive exPlanations
Sharepoint
Silhouette Analysis
Similarity Search
Single source of truth
sklearn datasets
Sklearn Pipiline
Small Language Models
Smart Grids
SMOTE (Synthetic Minority Over-sampling Technique)
SMSS
Snowflake
Snowflake Schema
Snowflake vs Hadoop
Software Design Patterns
Software Development Life Cycle
Software Development Portal
spaCy
SparseCategorialCrossentropy or CategoricalCrossEntropy
Spearman vs Pearson Correlation
Specificity
Spreadsheets vs Databases
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
Stored Procedures
Streamlit
Strongly vs Weakly typed language
Structuring and organizing data
Summarisation
Supervised Learning
Support Vector Classifier (SVC)
Support Vector Machines
Support Vector Regression
SVM_Example.py
Symbolic computation
Sympy
syntactic relationships
t-SNE
T-test
Tableau
Technical Analysis of Named Entity Recognition
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
The Data Hierarchy of Needs
Thinking Systems
Time Series
Time Series Forecasting
Time Series Identify Trends and Patterns
Tokenisation
TOML
tool.bandit
tool.ruff
tool.uv
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
Types of Computational Bugs
Types of Database Schema
Types of Neural Networks
TypeScript
Typical Output Formats in Neural Networks
Ubuntu
UML
unittest
univariate vs multivariate
Unix
unstructured data
Unsupervised learning
Use Cases for a Simple Neural Network Like
Use of RNNs in energy sector
Utilities
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)
Webpages relevant
What are Data Processing Techniques (row-based, columnar, vectorized)?
What are the top Cloud Providers?
What is a Data Lake?
What is a Data Lakehouse?
What is a Data Product?
What is a Data Warehouse?
What is a Jinja Template?
What is a Lambda Architecture?
What is a Metric?
What is a policy in RL
What is a Push-Down?
What is a Soft Delete?
What is a Storage Layer / Object Store?
What is an In-Memory Format?
What is Apache Airflow?
What is Apache Spark?
What is Business Intelligence
What is Dagster?
What is Data Governance?
What is Data Integration?
What is Data Lineage?
What is Data Literacy?
What is Data Observability?
What is Data Quality?
What is data transformation?
What is declarative?
What is DevOps?
What is ETL?
What is Functional Programming?
What is Granularity
What is imperative?
What is Kubernetes?
What is Machine Learning?
What is MapReduce?
What is Master Data Management (MDM)?
What is Normalization?
What is OLAP (Online Analytical Processing)?
What is Reverse ETL?
What is Schema Evolution?
What is semi-structured data?
What is Slowly Changing Dimension?
What is SQL?
What is structured data?
What is the Big-O Notation?
What is the role of gradient-based optimization in training deep learning models.
What is YAML?
When and why not to us regularisation
Why and when is feature scaling necessary
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 is the Central Limit Theorem important when working with small sample sizes
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 Scheduled Tasks
Windows Subsystem for Linux
Word2vec
Word2Vec.py
WordNet
Wrapper Methods
Xaiver
XGBoost
Z-Normalisation
Z-Score
Z-Scores vs Prediction Intervals
Z-Test
Unix
Unix is a operating system.