- GCP Colab vs Workbench
- GCP Dataproc Api Example
- GCP Dataflow Api Example Python
- GCP Dataflow Api Example
- Random Forests
- Feature Importance in Decision Trees
- Decision Tree Regression
- Decision Trees Classification
- Encoding Text in Emojis
- Dynamic Time Warping
- Sensitivity Analysis
- Lexical vs Semantic Search
- Hash Map Resizing
- Linear Probing
- Apache Hadoop
- Apache Spark
- GCP Dataproc
- GCP Dataflow Flex Templates vs Classic Templates
- GCP Dataflow Templates
- GCP Dataflow
- Cloud Dataprep by Trifacta
- GCP Predictive CLV
- Programmatic Audience Segmentation
- The Programmatics Process
- Programmatics Concepts
- Programmatic Advertising
- Online Analytics
- The Buyer's Journey
- Diminishing Return
- Marketing Attribution
- Marketing Mix Models
- How SEO Works
- Advertising Adstock
- Marketing Glossary
- GCP Model Garden
- GCP Model Tuning
- GCP Prompt Design
- GCP Generative AI and Workflow
- GCP MLops and Workflow Automation
- GCP Model Serving
- GCP Model Development
- GCP Data Preparation
- GCP ML Workflow
- GCP Custom Training
- GCP AutoML
- GCP Vertex AI
- GCP Pre-Trained APIs
- GCP AI Development Options
- GCP Big Query
- GCP Model Categories
- GCP Structured vs Unstructured Data
- GCP Computational Power
- GCP Google Cloud Infrastructure
- GCP Responsible AI
- Database Index
- GCP Machine Learning Engineer Certification
- Anabolic and Catabolic Exercises
- Catabolism vs Anabolism
- Twelve Factor App - Admin Processes
- Twelve Factor App - Logs
- Twelve Factor App - Dev/Prod Parity
- Twelve Factor App - Disposability
- Twelve Factor App - Concurrency
- Twelve Factor App - Port Binding
- Twelve Factor App - Processes
- Twelve Factor App - Build, Release, Run
- Twelve Factor App - Backing Services
- Twelve Factor App - Config
- Twelve Factor App - Dependencies
- Twelve Factor App - Codebase
- Twelve Factor App
- Machine Learning and Random Variables
- Machine Learning Data Structures
- Why Machine Learning Works
- What is Machine Learning
- Learning machines
- ACID properties
- Bayesian Inference - PyMC example
- Bayesian Inference - Estimating the Parameter
- Bayesian Inference - Continuous Distributions
- Bayesian Inference - Discrete Distributions
- Bayesian Inference - Probability Distributions
- Bayesian Inference - introduction
- CORS Cross-Origin Resource Sharing
- DFS vs BFS
- Depth First Search
- Types of Graph
- Breadth First Search
- Adjacency List for Graphs
- Adjacency Matrix for Graphs
- Graph Data Structure
- Trie Data Structure
- Hash Function
- Hash Map Data Structure
- RB-tree Insertion
- Rotation in RB-trees
- Balancing Property of RB-trees
- Strongly Connected Graph
- Aperiodic Graph
- PageRank algorithm
- Markov Chains in Machine Learning
- Markov Chains
- MDE
- Red Black Tree
- Unbalanced Binary Search Tree
- Python Fixed Length VS Variable Length Variables
- Python Storage VS Memory
- Python Variable Packing
- Binary Tree Data Structure
- Tree Data Structure
- Linked List Data Structure
- Queue Data Structure
- Data structures
- Recursive Sets
- Decision Problem
- NP complete
- halting problem
- Deterministic Turing Machine
- Nondeterministic Turing Machine
- Non deterministic polynomial time
- CAGR
- Big O summary
- P algorithms
- Polynomial VS Exponential time
- selection sort algorithm
- quicksort algorithm
- insertion sort algorithm
- merge sort algorithm
- bubble sort algorithm
- binary search algorithm
- Big O Notation Formal Definition
- Big O Notation
- What is an algorithm
- html cheatsheet
- Currying
- Closures
- Referential transparency
- Pure Functions
- Classes VS Functions
- Functional programming
- Function signature
- Constructors in OOP
- Dry Code
- Clean Code
- gitignore
- Git remotes
- Git undoing changes
- Git rebase
- Git fast-forward merge
- Git merging
- Git branches
- Git configuration
- Git snapshot optimisation
- Git tree and blob
- Git basic plumbing
- Git commit history and logs
- Git stage and commit
- Git repos
- Git porcelain and plumbing
- Git workflow
- Git states
- Git tips and uses
- The Unix philosophy
- Shebang
- Difference between Bugs and Errors
- Parameters vs arguments
- Quick Python tips and facts
- Data Types
- Gotchas with SQLite in Production
- Yield pattern in Go
- Interview Roadmap
- Authenticity and Integrity
- Indistinguishability
- Symmetric Cryptography
- Cryptographic agility
- Data lifetimes
- Public Key Infrastructure
- Side channel attacks
- Memory, randomness and clock in secure systems
- Input sanitisation
- On errors in cryptographic systems
- Security Model
- Auditing
- Authorisation
- Authentication
- Cryptography basics
- Cryptographic glossary
- Dependency Injection
- Object Oriented Programming
- Software Design tips
- Systemd Timers
- Systemd Targets
- Systemd Services
- Systemd introduction
- Btrfs introduction
- Geo experiments
- sway setup
- Below the line marketing
- Above the line marketing
- Gross Rating Point
- Elm Architecture
- TLS handshake
- How does TLS work
- TLS certificate
- Transport Layer Security
- Protocol Stack
- TCP handshake
- Monkey Patching
- HTTP PUT method
- HTTP POST method
- HTTP methods
- HTTP status codes
- Anatomy of a HTTP message
- Example of HTTP/1 messages
- HTTP flow
- What is TCP
- What is HTTP
- What is JSON-RPC
- What is RPC
- What is the Language Server Protocol
- What is Heteroscedasticity
- Stratified Randomization
- Linear Time Majority Algorithm
- Unix domain sockets in Golang snippet
- Unix Pipes
- File Descriptors
- Network sockets in Golang
- Differences between Unix Domain Sockets and Network Sockets
- Network Sockets
- Unix Domain Sockets in Golang
- Unix Domain Sockets
- Manacher's algorithm
- Backtracking
- Regression testing
- Memoization
- Dynamic Programming
- Quasi-experiment design
- Definition of buffer
- Channels in Goroutines
- Goroutines
- Generic Types in Go
- Generic type parameters in Go
- Readers in Go
- Errors in Go
- Stringers interface in Go
- Type switches in Go
- Type assertions in Go
- The empty interface in Go
- Nil in Go
- Interface values with nil underlying values in Go
- Interface Values in Go
- Interfaces in Go
- Choosing a value or pointer receiver in Go
- Ad Frequency in general
- Facebook Ad Frequency
- Precordium and resuscitation
- Edmund Burke and the role of parliament in popular complaints
- Slouching is not bad
- The curse of conformism
- What is anarchism
- Methods on non struct-types
- Creating a slice with make
- Slice zero value
- Go slices length and capacity
- Go slices as reference to arrays
- Go Arrays
- Pointers to struct
- Go basic types
- About testing other's people code
- Comparing JSON
- Golden Files
- Marshalling
- Flow Engineering
- Clever code and obviousness-oriented programming
- How ideas are borne
- Eternal September
- Backus Naur Form (BNF)
- AI agents as distribution channels
- Synthetic Data
- Manchester Trip
- Unit tests VS Integration tests
- AI design patterns
- Liskov substitution principle
- Exiting in Go
- Building an executable in Go
- The init function in Go
- Compilation in Go
- Variadic Functions in Go
- Modifying result parameters after exit in Go
- Named result parameters in Go
- The defer keyword in Go
- Closures in Go
- Function literals in Go
- Functions as values in Go
- Functions in Go
- Eat the fish, Spit the bones
- Controlling nested loops with labels in Go
- Continue and Break in For loops in Go
- Init and Post statements in For loops in Go
- Loops in Go
- Switch expressions
- Go Switch cases
- Compound if statements in Go
- Early return
- Happy path
- If statements in Go
- Increment and decrement statements in Go
- Assigning more than one value in Go
- Declaration in Go
- Assignment statement in Go
- Statements in Go
- Iota constant in Go
- Defining constants in Go
- Use a map to represent a set in Go
- Unexported fields and cmp.Equal in Go
- Validating methods in Go
- Go maps
- Pointer methods in Go
- Go methods on non-local types
- WebAssembly (WASM)
- Copy-and-Patch JIT
- Just-in-Time JIT
- Analytics 360
- Export your GA data to BigQuery
- Integrations with GA
- Combine business data in GA
- Use GA data for ads personalization
- Control how data is used in GA
- Go pointers
- Go struct wrappers
- Go types and methods
- Sorting a slice in Go
- Non-existent keys in Go maps
- Updating struct elements inside a map in Go
- Link Google Ads and GA
- Audiences in GA
- Attribution modeling in GA
- Conversion modeling in GA
- Advertising Workspace in GA
- Why data might look different between Reports and Explore in GA
- Use Explore for Advanced Anaytics in GA
- Filters and Comparisons in GA reports
- Test coverage in Go
- User stories in development
- Writing Struct literals in Go
- Exported Identifiers in Go
- Composite values and structs in Go
- Shorthand assignment in Go
- Zero values and default values in Go
- Values and Variables in Go
- Blank identifier in Go
- Go main package
- Go test driven development process
- Fatalf and Errorf in Go testing
- One behaviour, one test
- Multiple values in Go functions
- Go slices
- Struct in Go
- Test cases
- Test driven feature design
- Initialize a go package
- Conditional expressions in Go
- want-and-got pattern
- Go tests
- Go modules
- Writing tests
- Ajax
- Get to know the Predefined Reports of GA4
- Understand Google Analytics Reports
- Manage your Google Analytics Conversions
- Manage and Filter the Data you collect
- Manage your Google Analytics Events
- Power your Reports with Dimensions and Metrics
- The Admin Menu of Google Analytics
- Confirm Data is being collected
- Set up your App for Data Collection
- Adguardhome Setup
- Fedora Server setup
- Homelab setup
- Python logging
- Caching
- Cache decorator python
- Terminal control flow
- Purchase Order
- Good investors
- Investment fund
- Target date fund
- How to get a rich life
- Key metrics for personal finance
- Excel flatten table
- Usenet
- Projects
- NAT
- Port Forwarding
- cgroups VS namespaces
- cgroups
- Linux Namespaces
- Virtual Machine
- Hypervisors
- Garbage collectors
- Stack Overflow
- Stack Data Structure
- Heap and Stack
- WebRTC
- Notepy ideas
- Setup data streams in GA
- GA Account structure
- GA and data
- Marketing Funnel
- What is web analytics
- Analysis of a Generalized Linear Mixed Model
- Analysis of a Linear Mixed Model
- Introduction to Mixed Effects Models
- Generalized Linear Models
- Introduction to Generalized Linear Models
- ART - non-parametric factorial ANOVA
- Optimistic initialization
- Decaying e-greedy
- Comparing stategies
- e-greedy
- Greedy Strategy
- Multi-armed bandits framework
- Exploration vs Exploitation
- Analyzing a factorial ANOVA
- Interaction effects
- Factorial ANOVA
- One-way repeated measures ANOVA
- ANOVA for within-subject in R - non-parametric
- ANOVA for within-subjects in R
- Wide vs Long format tables
- Counterbalancing repeated measures factors
- Description of One-Way Repeated Measures ANOVA
- Non-parametric One-Way ANOVA
- One-Way ANOVA
- Mann-Whitney test
- Data transformation when normality is violated
- Test the ANOVA assumptions
- Parametric vs Non-parametric Analyses
- Probability Distributions
- Snowball sampling
- Anova assumptions
- Running an A/B test
- Exerting control
- Measuring Results
- Confounding variables
- Designing for Experimental Control
- Independent Samples T-Test
- Variable types
- Measurement errors
- Example Analysis of an A/B test
- Two-sample tests of proportions
- Multiple categories test of proportions
- Exact, Asymptotic and Binomial Tests
- Report the result of a test
- Test of Proportions
- Basic Experiment Design Concepts
- Power of a test
- Questions asked when performing stat. test
- Frequentist vs Bayesian
- Structural subtyping
- Subtypes
- Types
- Simple subtyping