This python module can analyse cryptocurrency news for any number of coins given and return a sentiment. Can be easily integrated with a Trading bot to keep an eye on the news.

A collection of cryptocurrency news. Day to day financial charts of top 10 cryptocurrencies (Bitcoin, litecoin, monero ...). Google trend analysis and geographical interests. Bitcoin timeline. News collection from major cryptocurrency news sites such as CoinDesk, Bitcoin Magazine, etc.

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.

A real-time cryptocurrency analysis platform that combines technical analysis, sentiment analysis, volume analysis, news trends, and AI-powered predictions to provide comprehensive market insights and trading recommendations.

Ethereum has brought us tools like Smart Contract, Dapp and DAO creation, deployment, and management. We can easily pay someone without ever hitting the send button, access decentralized applications that cannot be censored or shut down and we can be part of Decentralized Autonomous Organizations. Mistakes were made, bugs were found, and recently, millions were lost. Some are calling The DAO hack the most expensive bug bounty ever held, but whoever said this certainly didn’t have his Ether invested in The DAO, as the situation regarding the seizure of the stolen funds doesn’t seem to be improving. The DAO happened, it failed, all we can do now is move on and learn from our mistakes. The problem is that if we keep learning from $50m errors, we’ll be the wisest and poorest people on the planet. That’s why it’s good to have training wheels sometimes. Ethereum is the perfect playground for skilled developers, but with its 700% value increase since creation, it has made Solidity, one of the programming languages in Ethereum, a very expensive toy. That’s why Krypton has launched an open invitation to all developers to poke around the Krypton blockchain and see what it has to offer. Krypton (KR) is an Ethereum-based cryptocurrency that allows users all the same features and perks (Smart Contracts, Dapps, DAOs, DACs) but for a lower “price.” Ethereum transaction fees, which are known as “Gas” are spent according to computational costs, which means that the higher the price of Ether, the higher those costs will be. covertress, the Krypton founder, and project manager said: We’ve contacted several faculties at major universities and invited them to use the KR chain for this purpose. All of this means that developers have a testbed for smart contracts and Dapps, which are less expensive to deploy in the KR blockchain, before moving on to a more mainstream environment like Ethereum. Krypton can now be considered as a “gateway” into Ethereum. The team isn’t planning to stay humble forever but will, however, take their time before deploying anything and becoming a direct competitor to Ethereum, allowing them to tighten up security and functionality before moving on to providing smart contracts and Dapp solutions for companies. If you liked this article follow us on Twitter @themerklenews and make sure to subscribe to our newsletter to receive the latest bitcoin and altcoin price analysis and the latest cryptocurrency news. Krypton – Smart Contracts and DAPPs Development for Business Systems & IoT Ticker: KR Algorithm: Dagger-Hashimoto Block Reward: 0.25 KR Block Target: 15 Seconds Listen Port: 17171 RPC Port: 8888 Total KR: ~2.669 Million Real-Time Total KR Ethereum-Based: Utilizes Smart Contracts, DAOs, DACs and DAPPs Block Explorer: http://explorer.krypton.rocks After years in the tech sector, for engineering, entertainment, travel & finance companies, I’ve turned my focus to blockchain and building a startup, Krypton, to help companies realize their distributed applications. $KR is my vision for an ultra-fast blockchain that can realize all of the features of Ethereum with fewer initial coins, faster speed and lower inflation. Krypton can do the same things as Ethereum. However, with Ethereum’s codebase being updated to safely deploy DAOs, DACs, and DAPPs, there will be an explosion of practical-use cases, especially in the Internet of Things field. Companies will be actively seeking experienced developers. KR is an alternative platform on which to deploy these new technologies and Krypton developers are ready to build these systems. Join me in connecting Ðapps devs with real-life applications. Let’s code the future. — covertress, Founder & Project Manager Krypton is now hiring Smart Contracts and Ðapps developers with experience in Solidity, JS, and node.js. Please join Krypton’s Slack to apply: http://slack.krypton.rocks

A sentiment analysis approach using news articles to predict cryptocurrency price.

A telegram bot that fetches multiple RSS cryptocurrency news feeds for sentiment analysis

Cryptocurrency trading platform prototype with real-time price charts, market data from multiple exchanges, portfolio tracking, buy/sell simulation, crypto news aggregation, and advanced technical analysis tools for digital asset traders.

An LLM-powered data analysis agent to efficiently search, analyze, and summarize cryptocurrency news using Groq, Llama 3, and Exa.

Crypto Price Predictor experimental project, a machine learning system designed to predict cryptocurrency price movements by combining real-time market data with news sentiment analysis.

A dashboard based on Plotly and Dash. It collects and displays a Sentiment Analysis time series on news about cryptocurrency, from various news sources.

Automate cryptocurrency news sentiment analysis using Python. Scrape news, analyze sentiment with NLP tools (VADER/TextBlob), and visualize trends to help understand market sentiment.

By July 2022, there are already more than 83 million people who have created unique Bitcoin wallets on Blockchain.com. A staggering 89% of American adults have heard of Bitcoin, but only 24% of Americans said they understand how cryptocurrency works. Millions of tweets and news are generated per day on Web3, but it is not easy for users to digest the vast quantity of information, and many of them are not even free on Web2. There are also thousands of DeFi in different blockchains, it is not easy to understand each of them. Understanding data from Web2 and Web3 has been a big challenge. Few protocols aggregate Web3 data and provide users a unique platform to visualize and analyze its data. Even fewer protocols allow users to manage their portfolios automatically and easily. Filos integrates AI and blockchain to rebuild finance, providing a community-focused decentralized platform. Our platform applies data analysis to Web3, helping users better manage their portfolios. Filos is designed to allow every user to participate and manage their portfolio easily without any tech barrier. To achieve this goal, our team will start from Ergo and Cardano, and ultimately will expand it to multiple chains like ETH, DOT, etc.

Get real-time cryptocurrency prices, market news, and trend analysis for Bitcoin, Ethereum, and more on InfoCrypto.

It is an MCP server written in Kotlin that provides information, analysis, news, and more related to cryptocurrency and financial using the Model Context Protocol (MCP). This project was developed to provide cryptocurrency news and coins prices to LLM surfaces in a standardized manner using the MCP protocol.

This project contains a Transformer-based deep learning model specifically designed for sentiment analysis in the field of cryptocurrency. The model is trained to analyze sentiment and emotions in finance-related news articles and predict their impact on cryptocurrency portfolio performance.

Cryptomind is a technical analysis bot for cryptocurrencies, such as Bitcoin. 💰📉 It uses data like moving averages 📊 and market news 📰 to recommend whether it's time to buy 🛒, sell 💸, or hold ⏸️ the asset. The bot helps make more informed decisions 🧠 based on current market conditions. 🌐📈

Cryptocurrency News Sentiment Analysis

Cryptocurrencies news data mining and analysis with NLP

A cryptocurrency trading bot that makes decisions based on real-time news sentiment analysis.

This cryptocurrency market sentiment analysis tool leverages a fine-tuned RoBERTa model for 98% accurate sentiment classification of cryptocurrency-related news articles. It uses Selenium and BeautifulSoup for web scraping news articles and provides insightful market sentiment analysis and data visualization

ML-based Cryptocurrency tracker - for Blockchain Hackathon. Sentiment analysis from Twitter and News sources to correlate and extrapolate currency exchange rates.

Crypto Info delivers tailored news on cryptocurrency, integrates uniswap tools working on and offering AI-driven market analysis recommendations to our users

CryptoPanicScraper is an asynchronous Python web scraper that gathers cryptocurrency-related news from [CryptoPanic](https://cryptopanic.com/). It provides sentiment analysis for the news headlines using the NLTK VADER sentiment analysis tool and caches the scraped data for future use.

FinBERT-based sentiment analysis system for cryptocurrency and financial news. Automates data ingestion, NLP processing, and correlation analysis every 3 hours. Deployed on a Linux server using MongoDB, SSH, and crontab for end-to-end automation.

MekaVerse is the one place in which you get all cryptocurrency prices, details, history of coins, price charts, news with a filter option to get specific coin news and social media analysis plus the whole world of NFTs marketplace & more.

A comprehensive real-time RSS monitoring service designed for cryptocurrency market analysis. This service continuously monitors major news sources and uses AI to classify articles based on their potential impact on crypto markets.

StockPredictor app is a powerful financial management tool incorporating LSTM and ARIMA time series analysis, sentiment analysis, real-time news updates, and cryptocurrency tracking. This innovative app assists users in making informed investment decisions by harnessing cutting-edge predictive algorithms.

This project aims to perform sentiment analysis and forecasting market trends of cryptocurrency news headlines using various Natural Language Processing (NLP) techniques and machine learning models such as CNN, RNN, LSTM and CNN with Word2Vec.

Koinix is the ultimate crypto tracker app designed to empower you with deep insights and keep you informed about the ever-evolving world of cryptocurrencies. With Koinix, you'll stay ahead of the curve, making informed decisions based on comprehensive fundamental analysis and up-to-the-minute news.