Community
Kaggle has a vibrant community of data scientists and machine learning practitioners who actively collaborate, share knowledge, and support each other.
Competitions
The platform hosts numerous competitions that allow users to test their skills on real-world problems, often with monetary prizes and recognition.
Datasets
Kaggle offers a vast repository of datasets that are readily available for analysis and can be used to practice and build models.
Kernels
Users can share and run code in the cloud using Kaggle Kernels, which provide a collaborative environment for analysis and model development.
Learning Resources
Kaggle provides numerous tutorials, courses, and micro-courses to help beginners and advanced users improve their skills in data science and machine learning.
Before you even build a model, you are going to need some kind of dataset. Usually a CSV or JSON file. You can build your own dataset from scratch using your own data, scrape data from somewhere, or use Kaggle. - Source: dev.to / 4 months ago
Kaggle: For data science and machine learning competitions. - Source: dev.to / 9 months ago
Need help with last minute python project (due today). Project involves choosing a dataset from kaggle.com to analyze and creating questions to answer through analyzing the data. I have a pdf file of the project guidelines if you want more details. Also on a budget. Source: almost 2 years ago
Next, you can do basic analysis of datasets in Python using libraries like pandas and scikit-learn. There's a lot of example datasets on kaggle.com. Source: almost 2 years ago
Also look into kaggle.com and participate in competitions, etc. This will be something you can show on your CV as real-world-experience while boosting your skills. Source: almost 2 years ago
Take a loot at the Open Images dataset or Kaggle. Source: almost 2 years ago
If you took a good database course and a good data science/data analytics/informatics course in college, you likely have the knowledge you need for the PBQs. Looking at the "Given a scenario..." objectives for the Data+, I think I would practice up basic SQL, then fire up PowerBI/RStudio/Jupyter Notebook/whatever your favorite visualization tool is and take some real-world data from kaggle.com and make some... Source: almost 2 years ago
I use datasets from huggingface.com and kaggle.com. These datasets come in various formats, some of which you can train your bot on to generate a LoRA. You can also download any book in txt format, like what you might find at archive.org and clean it up a bit to make it a reasonable training dataset that you can use to make a LoRA. Clean by deleting weird characters, html code and blank lines to give your model a... Source: about 2 years ago
For data analytics use try kaggle.com they have a intro tutorial. Source: about 2 years ago
I have already a degree in computer science, and I felt the same feeling that I'm feeling now. Studying something that Im quite fond of but the material that I get from my teacher is "too easy", I don't feel like I'm learning enough. While I was studying computer science I luckily discovered Kaggle.com. Through Kaggle I got a feeling that I excelled my learning in data science and got ahead of my class. This lead... Source: about 2 years ago
If you are looking for ML projects, you can checkout problems at kaggle.com . Kaggle has very nice problems, and solutions of many problems are also available online. You can practise them and learn from the available solutions. Source: about 2 years ago
Go to kaggle.com and learn data science. Or do some programming or AI checkout tensorflow.com. Or go to ocw.mit.edu and learn something cool from the number one university in the world. Source: about 2 years ago
This is not a book, but only an article. That is why it can't cover everything and assumes that you already have some base knowledge to get the most from reading it. It is essential that you are familiar with Python machine learning and understand how to train machine learning models using Numpy, Pandas, SciKit-Learn and Matplotlib Python libraries. Also, I assume that you are familiar with machine learning... - Source: dev.to / about 2 years ago
For data to fill your db with and practise on, kaggle is your friend. Source: about 2 years ago
Visit kaggle.com . Okhane beginner problem solve kora shuru korun. There are solutions posted with detailed answers. Try to understand them. Source: about 2 years ago
If you need test data for the database of your project, you can get a dataset from Kaggle or use a data generator. In the first case, if you need to process the data before inserting it into the database, you can use Pandas, a widely used Python library for data analysis. This library supports different formats, including CSV and JSON, and it also provides a method for inserting data into a SQL database. - Source: dev.to / about 2 years ago
Tried to host a database and gave up and stuck my data in some JSON files. I didn't scrap the data but found it on kaggle.com. Converted the spreadsheet to a JSON object and worked with that. Source: about 2 years ago
In my opinion, stop the learning loop and create simple to complex projects. During development kasi ng mga projects, may maeencounter ka pa na new knowledge as alam mo currently. When I'm still pursuing Data Analytics before (I'm a dev now btw), nagte-take ako ng mga challenges sa kaggle then nag c-create din ako ng analytics from the available datasets sa kaggle as practice and to hone my skills further. Also,... Source: over 2 years ago
Kaggle is also a site you can use to write and run models that has datasets available for use for free. Source: over 2 years ago
So the short answer is, go try something like kaggle.com and build anything at all, anything that interests you. You'll learn by doing it and find what types of problems you like solving. Then go do something completely different for your second project, etc. Don't get too focused on what you are solving, or that you need to specialize, especially at the beginning of your career. Source: over 2 years ago
I found kaggle.com very good. It's good basics and practical lessons using python libraries. Also they give certificates. All free. Source: over 2 years ago
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