Writing

Grounded Visual Reasoning on a Mac: a Corridor and a Drone Pan

LLM

mlx-vlm

Gemma-4

Falcon-Perception

MLX

local-inference

grounded-reasoning

video

tracking

Apple-Silicon

Two worked examples — a still photo and a drone video — running Falcon Perception and Gemma 4 locally on an M2 Max. Counts you can audit, from an agent that never does arithmetic in its head.

Apr 16, 2026

Brick Kilns from Above: Gemma 4 Calling Falcon Perception in a Loop

LLM

Falcon-Perception

Gemma-4

MLX

satellite

remote-sensing

brick-kilns

SentinelKilnDB

agent-loop

Hi-res ESRI imagery + Gemma 4 in the PR #926 agent loop on three brick-kiln classes. Twelve tiles, four Falcon queries each, three prompt variants — with per-tile mask grids and Gemma’s reasoning shown. 67% zero-shot, and the remaining 33% is instructive.

Apr 16, 2026

11 min

Why VLMs Lie About Numbers (and How to Fix It With Grounding)

LLM

Gemma-4

Falcon-Perception

MLX

local-inference

grounded-reasoning

multimodal

Gemma 4 sounds confident. Falcon Perception actually measures. Together they beat either alone — here is the evidence.

Apr 5, 2026

Google released Gemma 4 yesterday — open-weight multimodal models under Apache 2.0. In a companion post, we compared Gemma 4 and Gemini via the API. Here, we run Gemma 4 enti…

Gemma 4 Locally on Mac: Performance & Vision Benchmarks

LLM

Gemma-4

MLX

local-inference

multimodal

vision

Apple-Silicon

benchmarks

Apr 3, 2026

Google just released Gemma 4 — open-weight models (Apache 2.0) available directly through the Gemini API. Same SDK, same API key — just change the model name.

Gemma 4 vs Gemini: Open-Weight Models Meet the Gemini API

LLM

Gemma-4

Gemini

multimodal

vision

segmentation

comparison

Apr 3, 2026

Paper: Koh et al., Concept Bottleneck Models (ICML 2020)

Concept Bottleneck Models — MNIST Demo

interpretability

deep-learning

pytorch

MNIST

educational

Mar 12, 2026

Agentic Browsing with agent-browser

automation

tools

A hands-on guide to automating web browsing for AI agents using agent-browser CLI

Jan 15, 2026

Building AI Tool Servers with FastMCP

python

mcp

llm

tools

Learn how to build MCP servers with FastMCP - enabling LLMs like Claude to interact with your custom tools, databases, and APIs.

Jan 13, 2026

11 min

Brave Browser Setup for Teaching & Presentations

productivity

teaching

privacy

browser

Configure Brave browser to hide personal browsing history during classroom demos and presentations

Jan 4, 2026

In this notebook, we explore how Vision-Language Models excel at Optical Character Recognition (OCR) and structured document understanding. We’ll focus on:

VLM for OCR and LaTeX Generation: From Images to Structured Text

VLM

OCR

LaTeX

document-understanding

math-OCR

table-extraction

Jan 4, 2026

Terminal Optimization: A 2026 Refresh

terminal

productivity

macos

tools

A comprehensive terminal optimization covering security fixes, modern tooling, and performance improvements

Jan 3, 2026

In this notebook, we explore how Vision-Language Models (VLMs) can generate images, not just understand them. We’ll cover:

7 min

VLM-Guided Image Generation: From Text and Images to Pixels

VLM

image-generation

diffusion

stable-diffusion

CLIP

text-to-image

Jan 3, 2026

In this notebook, we’ll explore model compression techniques to make Vision-Language Models (VLMs) more efficient without significantly sacrificing performance. We’ll…

VLM Compression: Quantization, Pruning, and Distillation

VLM

compression

quantization

pruning

distillation

optimization

Jan 2, 2026

We’ve built VLMs that can describe images, detect objects, answer questions, and even outline objects with polygons. But what if we want to modify images using natural…

Teaching VLMs to Edit Images with Natural Language

VLM

image-editing

instruction-following

PIL

computer-vision

multimodal

Jan 1, 2026

In our VLM series, we’ve built models that can caption, detect objects, answer questions, and reason step-by-step. But what if we want to:

Visual Grounding and Polygon Segmentation with VLMs

VLM

visual-grounding

segmentation

referring-expression

polygon

deep-learning

Dec 31, 2025

In our VLM series, we’ve built models that can caption images, detect objects, answer questions, and handle multiple tasks. But can they reason about what they see?

Chain-of-Thought Visual Reasoning with VLMs

VLM

chain-of-thought

reasoning

visual-reasoning

multimodal

deep-learning

Dec 30, 2025

Brick kilns are a significant source of air pollution in India, particularly in the Indo-Gangetic Plain. Monitoring these kilns for environmental compliance is challenging…

Brick Kiln Detection using SAM3 and Satellite Imagery

SAM3

geospatial

object-detection

satellite-imagery

segmentation

environmental-monitoring

Dec 29, 2025

In the multi-task VLM notebook, we built a model that handles caption, OD, and VQA - but it requires explicit task prompts:

Intelligent Task Routing for Multi-Task VLMs

VLM

task-routing

auto-detection

classifier

multimodal

deep-learning

educational

Dec 28, 2025

When to clear memory: - After training/evaluation before starting a new notebook - When switching between large models - If you get CUDA out of memory errors

Multi-Image Vision-Language Model: Compare, Reason, and Understand

VLM

multi-image

interleaved

multimodal

deep-learning

educational

Dec 27, 2025

When to clear memory: - After training/evaluation before starting a new notebook - When switching between large models - If you get CUDA out of memory errors

Multi-Task Vision-Language Model: Caption, Detect, and Answer

VLM

multi-task

instruction-tuning

multimodal

deep-learning

educational

Dec 26, 2025

In the previous notebook, we built a minimal Vision-Language Model (VLM) from scratch and trained it on image captioning. The model learned to describe images in natural…

Instruction Fine-Tuning a VLM for Object Detection

VLM

instruction-tuning

object-detection

multimodal

deep-learning

educational

Dec 25, 2025

In previous notebooks, we: 1. Built a minimal VLM from scratch and trained it for image captioning 2. Instruction fine-tuned it for object detection with JSON output

Instruction Fine-Tuning a VLM for Visual Question Answering

VLM

instruction-tuning

VQA

multimodal

deep-learning

educational

Dec 25, 2025

Vision-Language Models (VLMs) have revolutionized how AI systems understand and reason about images. Models like GPT-4V, LLaVA, and Gemini can describe images, answer…

Building a Minimal Vision-Language Model from Scratch

VLM

vision-language

multimodal

deep-learning

transformers

educational

Dec 24, 2025

Consider this realistic scenario:

Fine-Tuning FunctionGemma for Multi-Table Data Analysis

LLM

fine-tuning

function-calling

gemma

data-analysis

SQL

Dec 24, 2025

Meta’s SAM3 introduces text-based prompting for segmentation - just describe what you want to segment. This notebook shows:

SAM3 + Gemini: Intelligent Image Segmentation

SAM3

Gemini

segmentation

vision

multimodal

Dec 23, 2025

In the previous post, we explored SAM3’s image segmentation. Now let’s use SAM3 for video tracking - following a tennis ball across frames using just a text prompt.

SAM3 Video Tracking: Following a Tennis Ball

SAM3

video

tracking

segmentation

Dec 23, 2025

Gemini’s code execution with images reveals how AI thinks. Instead of just getting an answer, you see:

Gemini Code Execution: See How AI Thinks, Codes, and Analyzes Images

LLM

Gemini

code-execution

computer-vision

reasoning

Dec 19, 2025

Brick kilns are a significant source of air pollution in India, and monitoring their temporal patterns across multiple locations is crucial for environmental management.…

Multi-Location Temporal Brick Kiln Analysis Using Async Gemini 3 Pro API

LLM

Gemini-3-Pro

satellite-imagery

temporal-analysis

async

environmental-monitoring

Dec 17, 2025

We often need to process multiple images. The question is: What is the fastest way to do it?

Gemini API Performance: Sequential vs Async vs Single-Prompt

LLM

Gemini

Performance

Batching

Python

Dec 12, 2025

In a previous post, we explored Google’s Gemini 3 Pro multimodal capabilities. The model showed impressive performance on object detection, segmentation, and complex visual…

Testing Gemini 3 Pro: Are VLMs Still Blind and Biased?

LLM

Gemini-3-Pro

vision

VLM

benchmarks

evaluation

Dec 10, 2025

Multimodal AI models can understand and generate content across different types of data—text, images, video, audio, and documents—through a unified interface. This notebook…

Gemini-3-Pro: Mastering Multimodal AI Capabilities

LLM

Gemini-3-Pro

multimodal

vision

audio

video

object-detection

Dec 6, 2025

In this post, we compare different approaches for extracting structured information from text using two tasks:

Structured Outputs: Extraction vs Classification with LLMs

LLM

structured-generation

evaluation

Nov 26, 2025

Google’s Alpha Earth project represents a breakthrough in satellite imagery analysis by providing pre-trained deep learning embeddings of Earth’s surface. These embeddings…

Exploring Satellite Embeddings with Google’s Alpha Earth

satellite-imagery

deep-learning

earth-observation

google-earth-engine

Nov 26, 2025

Handling Missing Input Channels with Mask-Aware Neural Networks

machine learning

deep learning

missing data

robust models

Learn how to build neural networks that gracefully handle missing input channels by explicitly encoding missingness patterns

Oct 29, 2025

Vector Search with Text and Images

Understanding vector databases through text and image search

Oct 7, 2025

Using REST APIs in Google Sheets with Apps Script

Learn how to call REST APIs from Google Sheets using a custom Apps Script function.

Aug 24, 2025

DINOv2 vs CNN: Transfer Learning vs Training from Scratch

Deep Learning

Computer Vision

Comparing DINOv2 fine-tuning vs training CNN from scratch for binary image classification

Aug 17, 2025

Visualizing ERA5 Data

Visualizing ERA5 data grid coverage over India

Aug 13, 2025

Temperature Scaling in Softmax: Controlling Randomness in Language Models

deep learning

natural language processing

softmax

temperature scaling

text generation

Exploring how temperature scaling affects the randomness and diversity of language model outputs through mathematical analysis and interactive visualizations

Jul 9, 2025

Multi-Image Classification with VOC Dataset Visualization

computer vision

deep learning

multi-label classification

data visualization

Visualizing and filtering multi-image classification samples from the VOC dataset for improved training data quality

Jul 7, 2025

Logit Masking for Sleep Stage Classification

machine learning

deep learning

sleep

sequence modeling

Demonstrating how logit masking enforces valid transitions in sleep stage classification

Jul 4, 2025

Here are some useful Slack tips to improve your team communication and channel management.

Slack Tips for Better Team Management

productivity

tools

Jun 30, 2025

Linux Remote Server Setup with uv and CUDA

setup

linux

remote

development-environment

gpu

cuda

Setting up Python Environment on Linux Remote Servers with GPU Support

Jan 15, 2025

Faster Quarto Builds with Incremental Rendering and Caching

quarto

github-actions

caching

performance

Tired of waiting 5+ minutes for Quarto to rebuild all 145 posts when you only changed one? Here’s how to make GitHub Actions only rebuild what actually changed.

Jan 8, 2025

8 min

Parallel File Transfer Over SSH When You Have Thousands of Files

ssh

scp

performance

terminal

Transferring large projects with thousands of small files over SSH can be painfully slow. Here’s how we solved it with parallel transfers.

Jan 7, 2025

Keyboard shortcuts on Mac

setup

macos

shortcuts

productivity

keyboard-shortcuts

workflow

Keyboard shortcuts on mac

Jun 12, 2024

Object detection

computer-vision

object-detection

deep-learning

neural-networks

yolo

pytorch

from ultralytics import YOLO, checks, hub
import pandas as pd

Time Series Forecasting - Comparing MLP and Transformer Models

time-series

forecasting

deep-learning

transformers

pytorch

import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import torch
import torch.nn as nn
import torch.nn…

Character-Level Attention Mechanism for Name Generation

1165 rows × 1 columns

Character-Level RNN for Name Generation

1165 rows × 1 columns

Attention in Sequence to Sequence

attention-mechanism

sequence-to-sequence

deep-learning

neural-networks

transformers

nlp

pytorch

import torch
import torch.nn as nn
import torch.optim as optim
from torch.utils.data import DataLoader, TensorDataset
import numpy as np
import matplotlib.pyplot as plt

Sampling Distribution Analysis - Mean vs Standard Deviation

import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import torch
import torch.nn as nn
import torch.nn…

May 7, 2024

Mixture of Experts

import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import torch
import torch.nn as nn
import torch.nn…

Jan 18, 2024

Logo

import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
%config InlineBackend.figure_format = 'retina'

Jan 2, 2024

Basic Neural Process

import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
import torch
import torch.nn as nn
import torch.nn.functional as F
%config…

Dec 28, 2023

Using a neural network as a covariance function

import torch
import torch.nn as nn
import matplotlib.pyplot as plt
import numpy as np
# Retina mode
%config InlineBackend.figure_format = 'retina'

# Create…

Dec 22, 2023

Towards Transformers

transformers

attention-mechanism

deep-learning

neural-networks

nlp

sequence-modeling

pytorch

import tiktoken

encoding = tiktoken.get_encoding("cl100k_base")

encoding.encode("Hello World! This is a simple notebook")

[9906, 4435, 0, 1115…

Dec 21, 2023

Naive implementation of Strassen’s algorithm

import numpy as np 
import time
import matplotlib.pyplot as plt
import pandas as pd
# Retina display
%config InlineBackend.figure_format = 'retina'

log_size …

Dec 20, 2023

import matplotlib.pyplot as plt
import torch

%matplotlib inline
%config InlineBackend.figure_format='retina'

# Download some MNIST to demonstrate…

Jul 12, 2023

Trees using NetworkX

import networkx as nx
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

%matplotlib inline

# Retina display
%config InlineBackend.figure_format =…

Jun 12, 2023

Positional Encoding

import numpy as np
import matplotlib.pyplot as plt
import torch
import seaborn as sns
import pandas as pd

dist =torch.distributions

sns.reset_defaults()
sns.set_co…

Jun 9, 2023

Bayesian Active Learning with Disagreement (BALD)

import numpy as np
import matplotlib.pyplot as plt
import torch
import seaborn as sns
import pandas as pd

dist =torch.distributions

sns.reset_defaults()
sns.set_co…

May 26, 2023

PINNs are a class of neural networks for solving partial differential equations. They are trained to minimize the residual of the differential equation, and the boundary and…

PINN

May 5, 2023

Gradient wrt input for a simple model for adversarial attacks

SIREN paper implementation

Reconstruction from ReLU

Reconstruction from Sine

Apr 28, 2023

In this post, I’m noting some observations from the SIREN paper.

SIREN paper

Apr 27, 2023

Heteroskedastic and Homoskedastic MLPs in PyTorch for regression

Tensorboard

import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim

import numpy as np
import matplotlib.pyplot as plt

from torch.utils.da…

Mar 21, 2023

Residual Connections in PyTorch

import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim

import numpy as np
import matplotlib.pyplot as plt

from torch.utils.da…

Mar 18, 2023

In this post, we look at AutoPyTorch, a framework for automated machine learning.

AutoML PyTorch

automl

neural-architecture-search

hyperparameter-optimization

automated-machine-learning

pytorch

Feb 25, 2023

Stacking (Meta Learning)

Feb 22, 2023

In this post, we study a simple meta learning technique called Stacking

Stacking (Ensemble Learning)

Feb 21, 2023

Second order Taylor series expansion of a function f around a point (x0, y0) is given by (when using the vector notation)

Multivariate Taylor Series

Feb 20, 2023

In this notebook, we will show how to compare different GP libraries to give the same loss for a simple GP regression problem.

Comparing GP libraries

Feb 6, 2023

Understanding Singular Value Decomposition with Visualizations

linear-algebra

matrix-decomposition

dimensionality-reduction

visualization

jax

from jax import vmap, jit, grad, vmap
import jax.numpy as jnp

# Enable 64-bit mode
from jax.config import config
config.update("jax_enable_x64", True)
import matplotl…

Feb 1, 2023

This is a work in progress. I will be adding more content to this post in the coming days.

Conformal Prediction

Jan 19, 2023

VSCode Settings and Tips

vscode

Shortcut	Action
Cmd + Shift + P	Open command palette
Ctrl + `	Toggle terminal
Cmd + B	Toggle sidebar
Cmd + Ctrl + F	Toggle full screen

Jan 17, 2023

Binomial and Poisson distribution

import jax.numpy as jnp
import jax
from jax import random
import tensorflow_probability.substrates.jax as tfp
tfd = tfp.distributions
import pandas as pd

import matpl…

Nov 20, 2022

Some useful tidibts in sympy

Nov 9, 2022

Autoencoders in JAX

A programming introduction to Autoencoders in JAX

Nov 4, 2022

Calibration

Probability Calibration

Oct 27, 2022

Multi-output Gaussian Process

Oct 25, 2022

This is the first post in a Quarto blog. Welcome!

Welcome To My Blog

news

Sep 14, 2022

Tristan O’Malley

Audio Filtering

import numpy as np
import matplotlib.pyplot as plt
import torch
import seaborn as sns
from functools import partial

sns.reset_defaults()
sns.set_context(context="ta…

Feb 24, 2022

Coordinate descent failure example

Pyro Conditioning

import numpy as np
import matplotlib.pyplot as plt
import torch
import seaborn as sns
import pandas as pd
import pyro

dist =pyro.distributions

sns.reset_defaults()
…

Feb 20, 2022

Probabilstic PCA using PyTorch distributions

import numpy as np
import matplotlib.pyplot as plt
import torch
import seaborn as sns
import pandas as pd

dist =torch.distributions

sns.reset_defaults()
sns.set_co…

Feb 17, 2022

Linear Regression using Pyro

import numpy as np
import matplotlib.pyplot as plt
import torch
import seaborn as sns
import pandas as pd

t_dist =torch.distributions

sns.reset_defaults()
sns.set_…

Feb 17, 2022

Drawing graphical models

Logistic Regression using PyTorch distributions

import numpy as np
import matplotlib.pyplot as plt
import torch
import seaborn as sns
import pandas as pd

dist =torch.distributions

sns.reset_defaults()
sns.set_co…

Feb 14, 2022

GMM

mixture-models

clustering

expectation-maximization

probabilistic-models

unsupervised-learning

import torch
dist = torch.distributions
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
%matplotlib inline

Feb 14, 2022

Let us first look at G1. Look at the illustration below. We have a normal distribution \(p\) and two other normal distributions \(q_1\) and \(q_2\). Which of \(q_1\) and \(q_…

Variational inference

variational-inference

bayesian

approximate-inference

probabilistic-models

optimization

Feb 12, 2022

Multiplying a matrix A with a vector x transforms x

Matrix as transformation and interpreting low rank matrix

Feb 11, 2022

\(\hat{\theta}_{MAP}=\dfrac{n}{n+\sigma^{2}} \bar{x}+\dfrac{\sigma^{2}}{n+\sigma^{2}} \mu\)

Maximum A-Posteriori (MAP) for parameters of univariate and multivariate normal distribution in PyTorch

PyTorch

Feb 11, 2022

Let us generate some normally distributed data and see if we can learn the mean.

Maximum Likelihood Estimation (MLE) for parameters of univariate and multivariate normal distribution in PyTorch

PyTorch

Feb 9, 2022

Autograd in JAX and PyTorch

JAX

PyTorch

import torch
from jax import grad
import jax.numpy as jnp

Feb 9, 2022

We will be studying the problem of coin tosses. I will not go into derivations but mostly deal with automatic gradient computation in TF Probability.

Coin Toss (MLE, MAP, Fully Bayesian) in TF Probability

TFP

Feb 7, 2022

In this notebook I’ll talk about sampling from univariate and multivariate normal distributions. I’ll mostly directly write the code and show the output. The excellent…

Simple Directed Graphical Models in TF Probability

TFP

Linear Regression in TF Probability using JointDistributionCoroutineAutoBatched

TFP

Sampling from univariate and multivariate normal distributions using Box-Muller transform

Feb 4, 2022

Let us first look at G1. Look at the illustration below. We have a normal distribution \(p\) and two other normal distributions \(q_1\) and \(q_2\). Which of \(q_1\) and \(q_…

Understanding KL-Divergence

Jan 29, 2022

Good reference https://tensorchiefs.github.io/bbs/files/21052019-bbs-Beate-uncertainty.pdf

Linear Regression in Tensorflow Probability

Jan 28, 2022

Let us generate some normally distributed data and see if we can learn the mean.

Testing out some distributions in Tensorflow Probability

Jan 26, 2022

Learning Gaussian Process regression parameters using mini-batch stochastic gradient descent

How to learn the parameters of a GP

Sep 3, 2021

Linear Regression from scratch in Julia

using Plots
theme(:default)

using LinearAlgebra
using LaTeXStrings

Sep 1, 2021

In this post, I will look at a simple application:

Probabilistic Programming in Pyro

Aug 20, 2021

Blurring an image selectively using Affinity Photo

setup

Blurring an image selectively using Affinity Photo

Jun 19, 2021

Audio filters

signal-processing

audio

filtering

digital-signal-processing

python

scipy

Audio filtering techniques and applications

Jun 18, 2021

Running Python scripts on server over ssh and getting back content

setup

python

ssh

remote-development

networking

terminal

Running Python scripts on server over ssh and getting back content

Jun 17, 2021

Some of my shortcuts on the iPad

setup

ipad

shortcuts

automation

productivity

ios

Some of my shortcuts on the iPad

Jun 16, 2021

My iPad Setup

setup

ipad

mobile-development

productivity

ios

My iPad computing setup

Jun 14, 2021

10 min

My Mac Setup

setup

macos

development-environment

productivity

tools

My Mac Setup

Jun 12, 2021

GAN

deep-learning

generative-models

adversarial-networks

neural-networks

keras

tensorflow

Implementation and visualization of Generative Adversarial Networks

May 31, 2021

Understanding Kernels in Gaussian Processes Regression

Using GPy and some interactive visualisations for understanding GPR and applying on a real world data set

Jun 26, 2020

Sampling from common distributions

From the ground up!

Apr 16, 2020

Learning Gaussian Process regression parameters using gradient descent

How to learn the parameters of a GP

Mar 29, 2020

Active Learning with Bayesian Linear Regression

A programming introduction to Active Learning with Bayesian Linear Regression.

Mar 28, 2020

Zeel Patel & Nipun Batra

8 min

Some experiments in Gaussian Processes Regression

Using GPy and some interactive visualisations for understanding GPR and applying on a real world data set

Mar 26, 2020

Some Neural Network Classification

A programming introduction to NNs.

Mar 8, 2020

Neural Networks from scratch

Simple scripts for downloading weather data

Mar 2, 2020

Excellent, now let us start from random weight initialisations and use backprop to come to our result

Learning neural network for XOR

Feb 28, 2020

Bayesian Linear Regression

bayesian

linear-regression

uncertainty-quantification

probabilistic-models

statistics

A programming introduction to Bayesian Linear Regression.

Feb 20, 2020

An Example Markdown Post

markdown

A minimal example of using markdown with fastpages.

Jan 14, 2020

Gaussian Processes

gaussian-processes

bayesian

uncertainty-quantification

probabilistic-models

kernel-methods

An interactive exploration of Gaussian processes.

Aug 20, 2019

16 min

Placement-Preparation-2018-1-HashMap

academia

HashMaps for programming interviews

Aug 18, 2018

Visualising Electricity Access Over Space and Time

sustainability

How is the world changing over the years!

Jun 26, 2018

Mapping location of air quality sensing in India

air quality

AQ sensing in India

Jun 21, 2018

Active Learning

A programming introduction to query by committee strategy for active learning

Jun 16, 2018

Signal denoising using RNNs in PyTorch

Denoising

Jan 13, 2018

CS Ph.D. lessons to my younger self

academia

Some personal reflections..

Jan 7, 2018

17 min

Neural Networks for Collaborative Filtering

Neural networks to learn the embeddings! and how to combine them

Dec 29, 2017

I have written a few posts earlier about matrix factorisation using various Python libraries. The main application I had in mind for matrix factorisation was recommender…

Recommend keras

recommendation-systems

collaborative-filtering

deep-learning

neural-networks

keras

tensorflow

Dec 18, 2017

Adagrad based matrix factorization

Adagrad optimizer for matrix factorisation

Aug 13, 2017

In this post, I’ll be using Adagrad for solving linear regression. As usual, the purpose of this post is educational. This link gives a good overview of Adagrad alongwith…

Linear regression adagrad vs gd

optimization

gradient-descent

adagrad

linear-regression

algorithms

Aug 12, 2017

A while back, I read this wonderful article called “Top 50 ggplot2 Visualizations - The Master List (With Full R Code)”. Many of the plots looked very useful. In this post…

Fifty ggplot python 1

visualization

data-visualization

ggplot

plotnine

python

data-analysis

Aug 2, 2017

Linear regression with prior (using gradient descent)

What if we start from some prior!

Jun 15, 2017

Data exploration using widgets in Matplotlib

visualisation

Exploring data in Matplotlib

Jun 14, 2017

Constrained Non-negative matrix factorisation using CVXPY

Constrained NMF using CVXPY!

Apr 21, 2017

Out of Tensor factorisation

Out of tensor factorisation

Apr 20, 2017

Out of matrix non-negative matrix factorisation

What if we to predict for entries not within the matrix?!

Apr 19, 2017

In the previous post, I had discussed regarding the EM algorithm from a programmer’s perspective. That blog post sparked an interesting discussion on Twitter which has led…

MCMC coins

bayesian

mcmc

monte-carlo

probabilistic-models

parameter-estimation

Jul 1, 2014

Latexify Matplotlib

visualisation

Towards amazing plots in research papers!

Jun 2, 2014

Programatically understanding Expectation Maximization

Maximize based on what you know, re-estimate!

Jun 1, 2014

Removing first 10% samples

Gibbs sampling

bayesian

mcmc

gibbs-sampling

probabilistic-models

sampling-methods

May 1, 2014

So you just recorded yourself saying a word and try to match it against another instance. The signals look similar, but have varying lengths and different activations for…

DTW

time-series

dynamic-time-warping

sequence-alignment

algorithms

distance-metrics

May 1, 2014

I took the Linear and Integer Programming course on coursera last year. It was a very well paced and structured course. In one of the modules, the instructors discussed…

Denoising

signal-processing

denoising

image-processing

feature-extraction

Sep 1, 2013

HMM Simulation for Continuous HMM

Simulating a continuous HMM

Jul 1, 2013

In this notebook we shall create a Hidden Markov Model [1] for the Unfair Casino problem [2]. In short the problem is as follows: In a casino there may be two die- one fair…

HMM simulate

hidden-markov-models

sequence-modeling

probabilistic-models

time-series

simulation

Jun 1, 2013

We’ve all grown up studying groupy by and aggregations in SQL. Pandas provides excellent functionality for group by and aggregations. However, for time series data, we need…

Aggregation timeseries

time-series

data-aggregation

data-analysis

pandas

visualization

May 1, 2013

Downloading weather data

visualisation

Simple scripts for downloading weather data

Apr 1, 2013