355 skills found · Page 5 of 12
hereandnowai / Master Langgraph Workflows In Python 20 Real World Agent Projects By Hereandnow AIUnlock the power of LangGraph v0.5.3 with 20 bite‑sized, beginner‑friendly agent projects—from chatbots and finance bots to multi-agent orchestrations. Developed by HERE AND NOW AI, this hands‑on tutorial delivers up‑to‑date Python code, practical business value, and scalable workflows built for today and beyond.
mahmutovichana / Google Image ScraperA Python script for automated image scraping from Google Images, ideal for creating datasets for machine learning and AI projects
Hariharanpugazh / Image To Text GeneratorMy first Python project - A desktop app that converts images to text using Google Gemini AI. Built during my AI & DS studies at SNS College without even owning a laptop. This is where my developer journey began.
ananya2001gupta / Bitcoin Price Prediction Using AI ML.Identify the software project, create business case, arrive at a problem statement. REQUIREMENT: Window XP, Internet, MS Office, etc. Problem Description: - 1. Introduction of AI and Machine Learning: - Artificial Intelligence applies machine learning, deep learning and other techniques to solve actual problems. Artificial intelligence (AI) brings the genuine human-to-machine interaction. Simply, Machine Learning is the algorithm that give computers the ability to learn from data and then make decisions and predictions, AI refers to idea where machines can execute tasks smartly. It is a faster process in learning the risk factors, and profitable opportunities. They have a feature of learning from their mistakes and experiences. When Machine learning is combined with Artificial Intelligence, it can be a large field to gather an immense amount of information and then rectify the errors and learn from further experiences, developing in a smarter, faster and accuracy handling technique. The main difference between Machine Learning and Artificial Intelligence is , If it is written in python then it is probably machine learning, If it is written in power point then it is artificial intelligence. As there are many existing projects that are implemented using AI and Machine Learning , And one of the project i.e., Bitcoin Price Prediction :- Bitcoin (₿ ) (founder - Satoshi Nakamoto , Ledger start: 3 January 2009 ) is a digital currency, a type of electronic money. It is decentralized advanced cash without a national bank or single chairman that can be sent from client to client on the shared Bitcoin arrange without middle people's requirement. Machine learning models can likely give us the insight we need to learn about the future of Cryptocurrency. It will not tell us the future but it might tell us the general trend and direction to expect the prices to move. These machine learning models predict the future of Bitcoin by coding them out in Python. Machine learning and AI-assisted trading have attracted growing interest for the past few years. this approach is to test the hypothesis that the inefficiency of the cryptocurrency market can be exploited to generate abnormal profits. the application of machine learning algorithms to the cryptocurrency market has been limited so far to the analysis of Bitcoin prices, using random forests , Bayesian neural network , long short-term memory neural network , and other algorithms. 2. Applications/Scope of AI and Machine Learning :- a) Sentiment Analysis :- It is the classification of subjective opinions or emotions (positive, negative, and neutral) within text data using natural language processing. b) It is Characterized as a use of computerized reasoning where accessible data is utilized through calculations to process or help the handling of factual information. BITCOIN PRICE PREDICTION USING AI AND MACHINE LEARNING: - The main aim of this is to find the actual Bitcoin price in US dollars can be predicted. The chance to make a model equipped for anticipating digital currencies fundamentally Bitcoin. # It works the prediction by taking the coinMarkup cap. # CoinMarketCap provides with historical data for Bitcoin price changes, keep a record of all the transactions by recording the amount of coins in circulation and the volume of coins traded in the last 24-hours. # Quandl is used to filter the dataset by using the MAT Lab properties. 3. Problem statement: - Some AI and Machine Learning problem statements are: - a) Data Privacy and Security: Once a company has dug up the data, privacy and security is eye-catching aspect that needs to be taken care of. b) Data Scarcity: The data is a very important aspect of AI, and labeled data is used to train machines to learn and make predictions. c) Data acquisition: In the process of machine learning, a large amount of data is used in the process of training and learning. d) High error susceptibility: In the process of artificial intelligence and machine learning, the high amount of data is used. Some problem statements of Bitcoin Price Prediction using AI and Machine Learning: - a) Experimental Phase Risk: It is less experimental than other counterparts. In addition, relative to traditional assets, its level can be assessed as high because this asset is not intended for conservative investors. b) Technology Risks: There is a technological risk to other cryptocurrencies in the form of the potential appearance of a more advanced cryptocurrency. Investors may simply not notice the moment when their virtual assets lose their real value. c) Price Variability: The variability of the value of cryptocurrency are the large volumes of exchange trading, the integration of Bitcoin with various companies, legislative initiatives of regulatory bodies and many other, sometimes disregarded phenomena. d) Consumer Protection: The property of the irreversibility of transactions in itself has little effect on the risks of investing in Bitcoin as an asset. e) Price Fluctuation Prediction: Since many investors care more about whether the sudden rise or fall is worth following. Bitcoin price often fluctuates by more than 10% (or even more than 30%) at some times. f) Lacks Government Regulation: Regulators in traditional financial markets are basically missing in the field of cryptocurrencies. For instance, fake news frequently affects the decisions of individual investors. g) It is difficult to use large interval data (e.g., day-level, and month-level data) . h) The change time of mining difficulties is much longer. Moreover, do not consider the news information since it is hard to determine the authenticity of a news or predict the occurrence of emergencies.
LinkedInLearning / Advanced Python Projects Build AI Applications 4465602 1This is a code repository for the LinkedIn Learning course Advanced Python Projects: Build AI Applications.
acetinkaya / AcetinkayaLecturer at Istanbul Gelisim University and AI Instructor at IGU Cyber Academy. Specializing in Python, deep learning, fuzzy logic, and algorithm development. Contributing open-source AI projects and educational content to support learning and innovation in artificial intelligence.
ameya1995 / ConstrictorAn agent-first dependency and blast-radius explorer for Python codebases. Generates structured, machine-readable dependency graphs that AI coding agents can query to understand code relationships, assess refactoring impact, and navigate complex projects autonomously.
virajbhutada / AI Database Query BotThis project seamlessly integrates a web-based interface with advanced AI to enable natural language interactions with a relational database. Utilizing Python, Streamlit for the frontend, and OpenAI for intelligent responses, it connects to a Postgres database for efficient data retrieval and features conversation history saving for easy reference.
dexmac221 / C64AIToolChainCommodore 64 toolchain using agents and Google Gemini 3 to develop assembler code for the Commodore 64. This project demonstrates a workflow where AI models can write, debug, and even playtest 6510 assembly games by providing them with a structured feedback loop involving the VICE emulator and Python-based visual verification.
alphafintech / QuantRank SP500 LLMA Python-based implementation of quantitative scoring frameworks for S&P 500 stocks, designed by ChatGPT and Gemini. The project ranks equities based on fundamentals and trend momentum using structured AI-generated strategies.
jonathanscholtes / Azure AI RAG Architecture React FastAPI And Cosmos DB Vector StoreThis project demonstrates deploying a secure, scalable Generative AI (GenAI) solution on Azure using a Retrieval-Augmented Generation (RAG) architecture and Azure best practices. Leveraging CosmosDB, Azure OpenAI, and a React + Python FastAPI framework, it ensures efficient data retrieval, security, and an intuitive user experience.
SukunaCodes / AI Video Shorts CreatorAI_Video_Shorts_Creator is a python-based tool that uses OpenAI's GPT-4 power to automatically analyze videos, extract the most interesting sections and crop them for improved viewing experience. This project combines the capabilities of GPT-4, FFmpeg, and OpenCV to automate the process of identifying highlights in videos.
KrishPatel1404 / Reddit Story Video GenRSCG is a Python-based project that automates the creation of short-form video content using Reddit data. It combines web scraping, AI text-to-speech (TTS), and code-based video editing to turn engaging Reddit threads into shareable videos.
vibheksoni / GrokAiChatA Python library for interacting with Grok AI through X's user account API. This project provides a clean interface for creating conversations, sending messages, and handling responses. Note: This uses the account user API, not the paid enterprise API. Grok AI is free for all X (Twitter) members.
LinkedInLearning / AI Projects With Python Tensorflow And Nltk 4512163This repo is for LINKEDIN LEARNING course AI Projects with Python, TensorFlow and NLTK
florijanqosja / Albanian ASRThis project is an AI-based transcription tool for the Albanian language. The tool is designed to automatically transcribe Albanian speech to text using Python.
qudus4l / Image Classifier To Identify Dog BreedsFirst AI programming with Python project
VukIG / Melanoma DetectorAn open source project dedicated towards providing high quality diagnosis for people unable to do so with a medical professional 📸 This app seamlessly blends React Native for the frontend with Python for the backend/AI model.
MarekIksinski / Multimodal Research Assistant OllamaThis project is a locally-run AI assistant built on Python and the Ollama framework
WebRevo / CHAT BUDDYExplore the ChatBuddy Project, a cutting-edge AI chatbot powered by Python, HTML, CSS, and JS. Engage in human-like conversations and enjoy an intuitive web interface for versatile applications!
