davedawitdave

30-Days-Of-Python

30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace.

A_B-Hypothesis-Testing

An advertising company is running an online ad for a client with the intention of increasing brand awareness. The advertiser company earns money by charging the client based on user engagements with the ad it designed and serves via different platforms. To increase its market competitiveness, the advertising company provides a further service that quantifies the increase in brand awareness as a result of the ads it shows to online users. The main objective of this project is to test if the ads that the advertising company runs resulted in a significant lift in brand awareness.

Agriculture-project

awesome-artificial-intelligence

A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.

awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

data-science-for-everyone

DataFrame

C++ DataFrame for statistical, Financial, and ML analysis -- in modern C++ using native types and contiguous memory storage

davedawitdave

Config files for my GitHub profile.

LLM

Large Language Models coupled with multiple AI capabilities to generate images and text as well as achieving human level performance on a number of tasks, the world is going through revolution in art (DALL-E, MidJourney, Imagine, etc.), science (AlphaFold), medicine, and other key areas. In-context learning, popularized by the team behind the GPT-3 LLM, brought a new revolution for using LLMs in so many tasks that the LLM is not trained for. This is in contrast to the usual fine-tuning that was required to equip AI models to perform better in tasks they are not trained for. With In-context learning, LLMs are able to readjust their performance on a task depending on the prompt - from structured input that can be considered partly a few-shot training and partly a test input. This has opened up many applications. This week’s challenge is to systematically explore strategies that help generate prompts for LLMs to do classification of web pages according to a few examples of human scores. You will be also required to compare responses and accuracies of multiple LLM models for a given promp

Network-security-analysis-and-botnet-prediction

davedawitdave/Agriculture-project

davedawitdave/davedawitdave

Config files for my GitHub profile.

davedawitdave/LLM

Large Language Models coupled with multiple AI capabilities to generate images and text as well as achieving human level performance on a number of tasks, the world is going through revolution in art (DALL-E, MidJourney, Imagine, etc.), science (AlphaFold), medicine, and other key areas. In-context learning, popularized by the team behind the GPT-3 LLM, brought a new revolution for using LLMs in so many tasks that the LLM is not trained for. This is in contrast to the usual fine-tuning that was required to equip AI models to perform better in tasks they are not trained for. With In-context learning, LLMs are able to readjust their performance on a task depending on the prompt - from structured input that can be considered partly a few-shot training and partly a test input. This has opened up many applications. This week’s challenge is to systematically explore strategies that help generate prompts for LLMs to do classification of web pages according to a few examples of human scores. You will be also required to compare responses and accuracies of multiple LLM models for a given promp

davedawitdave/Network-security-analysis-and-botnet-prediction

davedawitdave/30-Days-Of-Python

30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace.

davedawitdave/A_B-Hypothesis-Testing

An advertising company is running an online ad for a client with the intention of increasing brand awareness. The advertiser company earns money by charging the client based on user engagements with the ad it designed and serves via different platforms. To increase its market competitiveness, the advertising company provides a further service that quantifies the increase in brand awareness as a result of the ads it shows to online users. The main objective of this project is to test if the ads that the advertising company runs resulted in a significant lift in brand awareness.

davedawitdave/awesome-artificial-intelligence

A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.

davedawitdave/awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

davedawitdave/data-science-for-everyone

davedawitdave/DataFrame

C++ DataFrame for statistical, Financial, and ML analysis -- in modern C++ using native types and contiguous memory storage

davedawitdave/dvc-mlflow

davedawitdave/handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

davedawitdave/meriab21

davedawitdave/Movie_recommendation

davedawitdave/past

davedawitdave/Python

All Algorithms implemented in Python

davedawitdave/Python-Roadmap

Python Roadmap. Learn Python programming as your first programming language. Python for Absolute Beginners, Non-Tech Professionals, 15+ Projects, 30 Topics, 500+ Practice Questions, with Data Structures & Algorithms

davedawitdave/qutip-trail

QuTiP: Quantum Toolbox in Python

davedawitdave/sales-pridiction-analysis

davedawitdave/Telecom_Data_Analaysis

davedawitdave/Tensorflow

davedawitdave/trail2

davedawitdave/trail_1

davedawitdave/turkish-tweets-sentiment-analysis

This sentiment analysis project determines whether the tweets posted in the Turkish language on Twitter are positive or negative.

davedawitdave/Twitter-Data-Analysis

extracting twitter data