Machine learning requires large amounts of data to develop predictive models of the world. Help foster the development of machine learning by sharing or selling datasets you have developed or acquire new datasets to jumpstart your next project.
I have been working on a script for a year now that is live trading on an exchange on 250 crypto assets at a time. my script logs all the candles that are moving and evaluated against the previous price candle. If the price is higher as the previous price it is stated as an up candle logged.
Every new candle is logged inside a database , i exported the database as an csv.
It counted every candle from the beginning of the script untill the day when i uploaded this dataset info. The higher the candle number the higher the intereset in certain assets.
It also calculates the RSI , detect when an asset is spiking , min - max -average candle day price , 2D prince , 7D price , 30d price , 6M price , etc
It is a very interesting dataset for learning Machine learning or trying to understand the crypto market. with 50k lines of data you can try to predict when i crypto asset is rising or spiking.
Feel free to contact me if you have more questions related to my script or any values that are logged inside the database
I have been working on a script for a year now that is live trading on an exchange on 250 crypto assets at a time. my script logs all the candles that are moving and evaluated against the previous price candle. If the price is higher there is an up candle logged.
Every new candle is logged inside a database , i exported the database as an csv.
It counted every candle from the beginning of the script untill the day when i uploaded this dataset info. The higher the candle number the higher the intereset in certain assets.
It also calculates the RSI , detect when an asset is spiking , min - max -average candle day price , 2D prince , 7D price , 30d price , 6M price , etc. My script is still running from the day i uploaded this dataset. i worked very hard on this piece of code. This dataset is very iintereseting for machine learning or understanding the crypto market
This dataset is composed of approximately 820 Bengali poems each with their author and meter. The dataset may be pretty useful for any poem-related machine learning research and Bengali literature research works as well.
This dataset will help you apply your existing knowledge to great use. This dataset has 132 parameters on which 42 different types of diseases can be predicted.
This dataset consists of 2 CSV files. One of them is for training and the other is for testing your model.
Each CSV file has 133 columns. 132 of these columns are symptoms that a person experiences and the last column is the prognosis.
These symptoms are mapped to 42 diseases you can classify these sets of symptoms.
You are required to train your model on training data and test it on testing data.
*Images belongs to complex metallic surface of an special industrial part.
*Image Sets taken by 6 axis-robot with industrial specialized illumination, linescan camera system and telecentric lens.
*It contains variuos anomalities such as dust, scratches, bumps, painting failures, oil drops, water marks etc. on metal surface.
*Proposed set is perfect for training classification models and/or anomality detection models, it has been trained and tested very special anomaly detection model with %98 accuracy.
*Suggested automatic labeling can be created by request.
Knuckle Head Corporation is offering OCR images dataset for several industries like : Hotel, Cab Rental, Bar etc.
One Million OCR images dataset for several industries like : Hotel, Cab Rental, Bar etc. Every invoices are high quality images clicked by smartphones. We are covering USA and Indian business in those invoices.
There are three types of invoices (Well Light, Low Light and Shadow). Invoices are clicked in indoor and outdoor with different background.
Collection of articles from the category of Money Transfers including. Unique user_id, views, category, title, keywords, content, created_at, updated_at