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https://github.com/aiwithqasim/Free-Artificial-Intelligence-Resources

Welcome, to this Open Source Repository regarding FREE ARTIFICIAL INTELLIGENCE RESOURCE. Get Benefit from the free resources mention & kindly five STAR & FORK this so that it can get maximum Fame so that Everyone can take advantage.
https://github.com/aiwithqasim/Free-Artificial-Intelligence-Resources

ai article artificial-intelligence artificial-neural-networks blog data-science datascientist deep-learning freeresources hacktoberfest hecktoberfest2021 jobs machine-learning machine-learning-algorithms natural-language-processing nlp project python3 youtube

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Welcome, to this Open Source Repository regarding FREE ARTIFICIAL INTELLIGENCE RESOURCE. Get Benefit from the free resources mention & kindly five STAR & FORK this so that it can get maximum Fame so that Everyone can take advantage.

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README

        

![hacktoberfest](https://github.com/qasim1020/Free-Artificial-Intelligence-Resources/blob/main/Images/hacktoberfest.png)



Let's Contribute To Open-source


Hacktoberfest, in its 8th year, is a month-long celebration of open source software run by DigitalOcean. During the month of October, we invite you to join open-source software enthusiasts, beginners, and the developer community by contributing to open-source projects.

### *Completing the Challenge*

If you have previously never contributed to any open-source software then these steps will help you get started:

1. Go to Hacktoberfest [official website](https://hacktoberfest.digitalocean.com/) and sign in there using your GitHub.
2. Install git and setup in your computer. Download and install it from [here](https://git-scm.com/downloads).
3. Fork this repository by click the Fork button in the top right of this page or simply [click here](https://github.com/sharjeelyunus/hacktoberfest/fork).
4. Once it is forked, clone the repository in your computer. For this, copy the URL in the address bar, and use the following command:

```sh
git clone url_you_just_copied
```

4. Open this cloned repository in your preferred code editor. Also, open a terminal in this directory.
5. Now type in the following command in the terminal and replace `username` with your GitHub username.

```sh
git checkout -b username
```

6. Fill this block with necessary info of yourself.
```
{
"name": {YOUR_NAME},
"batch": {YOUR_BATCH_COMMENCEMENT_YEAR},
"major": {YOUR_DEPARTMENT},
"githubUsername": {YOUR_GITHUB_USERNAME},
"favoriteLanguage": {YOUR_FAVOURITE_PROGRAMMING_LANGUAGE}
}
```

7. Now add the above filled block to the array in `profiles.json` file

8. Once you have done all this, commit your changes to GitHub. You can do this with the following commands. Make sure you execute them in the precise order one after another in your terminal.

```sh
# copy and paste the following in the terminal
git add .

# copy and paste the following in the terminal after you have executed the previous command
git commit -m "hacktoberfest contribution"

# copy and paste the following in the terminal after you have executed the previous command
git push -u origin your_github_username
```

9. Now open the forked repository on your GitHub. You will see a yellow box at the top telling you that some changes are pushed. You will also see a button called `Compare & pull request`. Click on it.
10. Now add a title, some description! You have opened a pull request in this repository.

*You need to open **four** valid pull requests in order to complete the challenge. If you have performed the above steps, you have already opened one pull request. And you need only three more.*


>Note: Those repositories who have `hacktoberfest` as a label are considered for Hacktoberfest challenge only.





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![GitHub commit activity](https://img.shields.io/github/commit-activity/m/qasim1020/Free-Artificial-Intelligence-Resources?color=green&logo=Github)
![GitHub contributors](https://img.shields.io/github/contributors/qasim1020/Free-Artificial-Intelligence-Resources?color=green)
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### Get Published With AI

AI is a world’s leading multidisciplinary science Industry and the future of computing. Here I publish the best and free resources related to AI that have been suggested and read by thought-leaders and decision-makers around the world.

### Why should you contribute in this OpenSource Project ?


  • Because in AI Industry, your audience will be larger and we’ll make sure to spread the word not only on our social media channels, but our all networks as much as we could. We have seen a high engagement rate with high-quality articles.

  • You'll get to know the best and free resources including latest articles, news and be able to download resources

  • Grow with our community and be able to get feedback as necessary.



### Clearing the Confusion: AI vs Machine Learning vs Deep Learning Differences

Raise your hand if you’ve been caught in the confusion of differentiating artificial intelligence (AI) vs machine learning (ML) vs deep learning (DL).Bring down your hand, buddy, we can’t see it! Although the three terminologies are usually used interchangeably, they do not quite refer to the same things.

Andrey Bulezyuk, who is a German-based computer expert and has more than five years of experience in teaching people how artificial intelligence systems work, says that “practitioners in this field can clearly articulate the differences between the three closely-related terms.”

Therefore, is there a difference between artificial intelligence, machine learning, and deep learning?

Here is an image that attempts to visualize the distinction between them:





From above image, you can see DL is a subset of ML, which is also a subset of AI. Interesting, right?

So, AI is the all-encompassing concept that initially erupted, then followed by ML that thrived later, and lastly DL that is promising to escalate the advances of AI to another level. If you want to learn more then click here.

### FREE AI COURSES:

### FREE MACHINE LEARNING COURSES:



### FREE DATA SCIENCE COURSES:

### DATASET REPOSITORIES:

### COMPETITION PLATFORMS

### FREE DEEP LEARNING COURSES:



### DEEP EARNING BY MIT

  • Introduction to Deep Learning

  • Deep Sequence Modelling

  • Deep Learning for Computer Vision

  • Deep Generative Models

  • Deep Reinforcement Learning

  • Limitations and New Frontiers
  • ### STATISTICAL SOFTWARE FOR BEGINNERS

    ### FREE NLP COURSES:

    ### FREE MACHINE LEARNING IN GRAPHICS AND VISION COURSES

    ### AI RESEARCH AT BIG COMPANIES:

    ### DEVELOPER RESOURCES:

    ### AI CHEAT-SHEETS:

    ### YOUTUBE CHANNELS

    ### Course Downloads

    | Courses | School | Duration | Effort | Frequency | Prerequisites |
    | :-------------------------------------------------------------------------------------------------------------------------------- | :-----: | :------: | :--------------: | :--------: | :-----------------------: |
    | [Machine Learning Engineer Nanodegree](https://mega.nz/file/B1wUgaxJ#7DGzzv9qhEsFtSVhKoe8pkc1FcA0ZjIpldqDZoKyC1M) | Udacity | 3 months | 10 hours / week | self-paced | Intermediate Python & ML |
    | [AI for Healthcare Nanodegree Program](https://mega.nz/file/445mVAIT#O8_7ZquR2IEpv7vvs_B_iJVe8kdsat3rljzQOS8goG0) | Udacity | 4 months | 15 hours / week | self-paced | Intermediate Python & ML |
    | [Intel® Edge AI for IoT Developers Nanodegree Program](https://mega.nz/file/50pSUS4L#ihhAZMc2RpzK6l5HwUIrySAJ5CgY0hF3-Oroi5xcP2s) | Udacity | 3 months | 10 hours / week | self-paced | Intermediate Python & DL |
    | [AI Product Manager Nanodegree](https://mega.nz/file/F1hUXCIK#0uvURzJv2G3Il39or2PGr90loQUzh9CxqYiqOElxm20) | Udacity | 2 months | 2-5 hours / week | self-paced | none |
    | [Data Engineering Nanodegree](https://mega.nz/file/14hEiCQB#20knbJN_TMKCk9ckSAGMLpn2W8eURztAO-c-vs2mC1g) | Udacity | 5 months | 5 hrs / week | self-paced | Intermediate Python & SQL |

    ### Contribution Guideline:

    Feel free to open a PR if you feel like something needs to be added or you want to suggest something then your commit message should be in given format: added to -->resource_name-->section_name

    #### 🌟 Please star the repo so that it gets maximum exposure and more people can benefit from it!

    ### Terms & Conditions:



    • Please submit unpublished drafts with at least some Intresting Free resources anout AI.

    • We do not accept plagiarism. You may reference text from other sources, but it must be referenced ([1][2] and so on), and it cannot exceed 10% of an author’s content. Otherwise, we will reject your article.

    • Try to captivate your audience with a nice image — open-source images can be found at Pixabay, Unsplash, StockSnap, Flickr, Pexels, Burst, The Stocks.

    • Make sure your story has meaning — give more than you get.

    • No heavy self-promotion please, you can talk about your business, ventures, and others, yet, make sure that your audience stays on-board, and we prefer it to be on the bottom of the article after you have shared your insights and work.

    • Please utilize a grammar and readability tool such as Grammarly. If your article has too many grammatical errors, it won’t be accepted.

    ### Important Notice:

    All product names, logos, and brands are property of their respective owners. All company, product and service names used in this repository are for identification purposes only. Use of these names, logos, and brands does not imply endorsement.