Basics of Decision Trees
Decision Trees are the gateway to machine learning. They are easy to understand and relate to. However, do we know how they really work?
- machine learning fundamentals 4
- deep learning 3
- basics 3
- cnn 3
- classifier 3
- transfer learning 3
- computer vision 3
- resnet 3
- LLM 3
- linear algebra 2
- mathematics 2
- machine learning 2
- foundations 2
- RAG 2
- git 1
- github 1
- version control 1
- markdown 1
- jekyll 1
- pandas 1
- data analysis 1
- vectors 1
- matrices 1
- visual data analytics 1
- python 1
- seaborn 1
- decision trees 1
- entropy 1
- heuristics 1
- mnist 1
- gradient descent 1
- SGD 1
- neural network 1
- MNIST 1
- AWS 1
- enterprise search 1
- fine-tuning 1
- LLama2 1
- Colab 1
machine learning fundamentals
Visual Data Analysis in Python: Part 1
In this blog post, we explore visual data analytics, leveraging data visualization to uncover insights and patterns in our datasets. In this part 1 post, we ...
Machine Learning Fundamentals: Linear Algebra: Part 2-Matrices
In this blog post, we will try to understand matrices, their representation, properties and the various operations we can perform on them.
Machine Learning Fundamentals: Linear Algebra: Part 1-Vectors
In this blog post, we will try to understand vectors from their base representation, their properties and the various operations we can perform on vectors.
deep learning
Constructing a Neural Network to Classify Handwritten Digits
Build a Neural Network from scratch to recognize handwritten digits and later implement a Deep Neural Network using Pytorch
Understanding the Basics: Gradient Descent
Gradient Descent is an optimization algorithm that iteratively adjusts model parameters in the direction of steepest descent of the loss function to find the...
Machine Learning Foundations Through Q&A
we will try to understand the foundations of Machine learning & Deep learning in the form of Q&A.
basics
Constructing a Neural Network to Classify Handwritten Digits
Build a Neural Network from scratch to recognize handwritten digits and later implement a Deep Neural Network using Pytorch
Understanding the Basics: Gradient Descent
Gradient Descent is an optimization algorithm that iteratively adjusts model parameters in the direction of steepest descent of the loss function to find the...
Machine Learning Foundations Through Q&A
we will try to understand the foundations of Machine learning & Deep learning in the form of Q&A.
cnn
MiniProject: Emotion Classifier - Part3
Part3 of Building a Human Emotion Classifier - Front End GUI and Deployment
MiniProject: Emotion Classifier - Part2
Part2 of Building a Human Emotion Classifier using CNN by applying transfer Learning on Resnet18 implemented with FastAI
MiniProject: Emotion Classifier - Part1
Part1 of Building a Human Emotion Classifier using CNN by applying transfer Learning on Resnet18 implemented with FastAI
classifier
MiniProject: Emotion Classifier - Part3
Part3 of Building a Human Emotion Classifier - Front End GUI and Deployment
MiniProject: Emotion Classifier - Part2
Part2 of Building a Human Emotion Classifier using CNN by applying transfer Learning on Resnet18 implemented with FastAI
MiniProject: Emotion Classifier - Part1
Part1 of Building a Human Emotion Classifier using CNN by applying transfer Learning on Resnet18 implemented with FastAI
transfer learning
MiniProject: Emotion Classifier - Part3
Part3 of Building a Human Emotion Classifier - Front End GUI and Deployment
MiniProject: Emotion Classifier - Part2
Part2 of Building a Human Emotion Classifier using CNN by applying transfer Learning on Resnet18 implemented with FastAI
MiniProject: Emotion Classifier - Part1
Part1 of Building a Human Emotion Classifier using CNN by applying transfer Learning on Resnet18 implemented with FastAI
computer vision
MiniProject: Emotion Classifier - Part3
Part3 of Building a Human Emotion Classifier - Front End GUI and Deployment
MiniProject: Emotion Classifier - Part2
Part2 of Building a Human Emotion Classifier using CNN by applying transfer Learning on Resnet18 implemented with FastAI
MiniProject: Emotion Classifier - Part1
Part1 of Building a Human Emotion Classifier using CNN by applying transfer Learning on Resnet18 implemented with FastAI
resnet
MiniProject: Emotion Classifier - Part3
Part3 of Building a Human Emotion Classifier - Front End GUI and Deployment
MiniProject: Emotion Classifier - Part2
Part2 of Building a Human Emotion Classifier using CNN by applying transfer Learning on Resnet18 implemented with FastAI
MiniProject: Emotion Classifier - Part1
Part1 of Building a Human Emotion Classifier using CNN by applying transfer Learning on Resnet18 implemented with FastAI
LLM
Retrieval-Augmented Generation (RAG) with Llama 2 using Google Colab Free-Tier
Building a Q&A app capable of answering questions related to your enterprise documents using LLama2 7B Chat and Chroma Vector Database.
Optimizing Language Model Training: PEFT, LoRa, and QLoRa Techniques
techniques in fine-tuning large language models (LLMs) with significantly reduced RAM requirements
LLM Based Enterprise Search Solution using RAG In AWS
Building Large Language Models for Complex Enterprise Search Tasks using Retrieval Augmented Generation (RAG) - In AWS
linear algebra
Machine Learning Fundamentals: Linear Algebra: Part 2-Matrices
In this blog post, we will try to understand matrices, their representation, properties and the various operations we can perform on them.
Machine Learning Fundamentals: Linear Algebra: Part 1-Vectors
In this blog post, we will try to understand vectors from their base representation, their properties and the various operations we can perform on vectors.
mathematics
Machine Learning Fundamentals: Linear Algebra: Part 2-Matrices
In this blog post, we will try to understand matrices, their representation, properties and the various operations we can perform on them.
Machine Learning Fundamentals: Linear Algebra: Part 1-Vectors
In this blog post, we will try to understand vectors from their base representation, their properties and the various operations we can perform on vectors.
machine learning
Understanding the Basics: Gradient Descent
Gradient Descent is an optimization algorithm that iteratively adjusts model parameters in the direction of steepest descent of the loss function to find the...
Machine Learning Foundations Through Q&A
we will try to understand the foundations of Machine learning & Deep learning in the form of Q&A.
foundations
Constructing a Neural Network to Classify Handwritten Digits
Build a Neural Network from scratch to recognize handwritten digits and later implement a Deep Neural Network using Pytorch
Machine Learning Foundations Through Q&A
we will try to understand the foundations of Machine learning & Deep learning in the form of Q&A.
RAG
Retrieval-Augmented Generation (RAG) with Llama 2 using Google Colab Free-Tier
Building a Q&A app capable of answering questions related to your enterprise documents using LLama2 7B Chat and Chroma Vector Database.
LLM Based Enterprise Search Solution using RAG In AWS
Building Large Language Models for Complex Enterprise Search Tasks using Retrieval Augmented Generation (RAG) - In AWS
git
Git Commands Simplified: A Beginner’s Guide
In this beginner’s guide, I break down the essential Git commands into easy-to-understand explanations and practical examples. From initializing a repository...
github
Git Commands Simplified: A Beginner’s Guide
In this beginner’s guide, I break down the essential Git commands into easy-to-understand explanations and practical examples. From initializing a repository...
version control
Git Commands Simplified: A Beginner’s Guide
In this beginner’s guide, I break down the essential Git commands into easy-to-understand explanations and practical examples. From initializing a repository...
markdown
Markdown Cheatsheet: Quick Reference for Commonly Used Syntax
This cheatsheet provides a concise reference for frequently used Markdown formatting, helping you create beautiful, well-structured content with ease.
jekyll
Markdown Cheatsheet: Quick Reference for Commonly Used Syntax
This cheatsheet provides a concise reference for frequently used Markdown formatting, helping you create beautiful, well-structured content with ease.
pandas
Pandas: Data Analysis Essentials
This article outlines the essential Pandas methods for preliminary data analysis.
data analysis
Pandas: Data Analysis Essentials
This article outlines the essential Pandas methods for preliminary data analysis.
vectors
Machine Learning Fundamentals: Linear Algebra: Part 1-Vectors
In this blog post, we will try to understand vectors from their base representation, their properties and the various operations we can perform on vectors.
matrices
Machine Learning Fundamentals: Linear Algebra: Part 2-Matrices
In this blog post, we will try to understand matrices, their representation, properties and the various operations we can perform on them.
visual data analytics
Visual Data Analysis in Python: Part 1
In this blog post, we explore visual data analytics, leveraging data visualization to uncover insights and patterns in our datasets. In this part 1 post, we ...
python
Visual Data Analysis in Python: Part 1
In this blog post, we explore visual data analytics, leveraging data visualization to uncover insights and patterns in our datasets. In this part 1 post, we ...
seaborn
Visual Data Analysis in Python: Part 1
In this blog post, we explore visual data analytics, leveraging data visualization to uncover insights and patterns in our datasets. In this part 1 post, we ...
decision trees
Basics of Decision Trees
Decision Trees are the gateway to machine learning. They are easy to understand and relate to. However, do we know how they really work?
entropy
Basics of Decision Trees
Decision Trees are the gateway to machine learning. They are easy to understand and relate to. However, do we know how they really work?
heuristics
Basics of Decision Trees
Decision Trees are the gateway to machine learning. They are easy to understand and relate to. However, do we know how they really work?
mnist
Basics of Decision Trees
Decision Trees are the gateway to machine learning. They are easy to understand and relate to. However, do we know how they really work?
gradient descent
Understanding the Basics: Gradient Descent
Gradient Descent is an optimization algorithm that iteratively adjusts model parameters in the direction of steepest descent of the loss function to find the...
SGD
Understanding the Basics: Gradient Descent
Gradient Descent is an optimization algorithm that iteratively adjusts model parameters in the direction of steepest descent of the loss function to find the...
neural network
Constructing a Neural Network to Classify Handwritten Digits
Build a Neural Network from scratch to recognize handwritten digits and later implement a Deep Neural Network using Pytorch
MNIST
Constructing a Neural Network to Classify Handwritten Digits
Build a Neural Network from scratch to recognize handwritten digits and later implement a Deep Neural Network using Pytorch
AWS
LLM Based Enterprise Search Solution using RAG In AWS
Building Large Language Models for Complex Enterprise Search Tasks using Retrieval Augmented Generation (RAG) - In AWS
enterprise search
LLM Based Enterprise Search Solution using RAG In AWS
Building Large Language Models for Complex Enterprise Search Tasks using Retrieval Augmented Generation (RAG) - In AWS
fine-tuning
Optimizing Language Model Training: PEFT, LoRa, and QLoRa Techniques
techniques in fine-tuning large language models (LLMs) with significantly reduced RAM requirements
LLama2
Retrieval-Augmented Generation (RAG) with Llama 2 using Google Colab Free-Tier
Building a Q&A app capable of answering questions related to your enterprise documents using LLama2 7B Chat and Chroma Vector Database.
Colab
Retrieval-Augmented Generation (RAG) with Llama 2 using Google Colab Free-Tier
Building a Q&A app capable of answering questions related to your enterprise documents using LLama2 7B Chat and Chroma Vector Database.