I'm a Philonoist, and this is my website.
Here, you can find my projects and published blogs.
CatBoost is one of the best ML algorithms for tabular data. In this blog, we will try to understand the internal workings of CatBoost.CatBoost is an open-source gradient boosting algorithm, developed by Yandex.
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In this blog, we will understand the different ways to use LLMs on CPU. We will be using Open Source LLMs such as Llama 2 for our set up. And Create a Chat UI using ChainLit.
For Running the Large Language Models (LLMs) on CPU, we will be using
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Best practices for writing better code in Python.
This blog will help the beginners in python to write efficient and neat code. Even if you are an intermediate level programmer in python, I do recommend you to go through this blog Read More
In this blog, we will cover the fundamentals you need to know to get started with data science.
When analyzing data, two methods are most commonly used in statistics these are: Read More
In this blog, we will understand variance and get an insight why do we divide by n-1 without going into any mathematical proof.
Our objective is to describe the spread of data. The maximum and minimum value i.e., Read More
Python, C++, MySQL, MongoDB.
AWS, Github Actions, Docker, Kubernetes, W&B, MLflow, DVC, DagsHub.
PyTorch, Hugging Face, Tensorflow, Keras, Scikit-Learn, XGBoost, CatBoost, NLTK, Gensim, statsmodels, LangChain, FastAPI, Flask, Pandas, Numpy, Matplotlib, Seaborn, Plotly, Plotly's Dash, Beautiful soup, Scrapy.
Supervised: Linear Regression, Elastic-Net Regression, Logistic Regression, KNN, Decision Trees, Naive-Bayes, SVM, Ensemble Methods.
Unsupervised: K-Means, K-Medoids, K-Modes, Hierarichal Clustering, DBSCAN, PCA.
Deep Learning: ANN, CNN, Object Detection, Segmentation, GANS, Diffusion models, RNNs, Transformer and LLMs.
Recommendation systems
Exponential Smoothing, ARIMA, SARIMAX, VAR, ARCH, GARCH.
Vs Code, Jupyter Notebook, PyCharm
2019 - 2023
Moradabad Institute of Technology
