You need somebody in your team who knows math for real.Learn ML (pro) ✅ MML book: <a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbDZtNlJpeXo2dUVUOENYYzR6T3k2cFFvMjFfZ3xBQ3Jtc0trdFoxeldyWEhSSHY1elFPeXY4WUY0WVFQdWNsVEdPTWNyRzdzZjFXdVdvd3RvRGlaQm9ZYVlVdG1HdFhoeHNISXY0Z3BieERGcmFqVlJzMDUtSzB6Rm5BM2dBUlVFSzZjXzZEWEY5a2ZVQzNUbUVOcw&q=https%3A%2F%2Fmml-book.github.io%2Fbook%2Fmml-book.pdf&v=7q_OJvQQ7vY">https://mml-book.github.io/book/mml-b...</a> Supplements:✅ 3B1B LA: <a href="https://www.youtube.com/watch?v=fNk_zzaMoSs&list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab&index=1&t=0s">https://www.youtube.com/watch?v=fNk_z...</a> ✅ 3B1B Calculus: <a href="https://www.youtube.com/watch?v=WUvTyaaNkzM&list=PLZHQObOWTQDMsr9K-rj53DwVRMYO3t5Yr&index=1&t=0s">https://www.youtube.com/watch?v=WUvTy...</a> ✅ chapter 5: <a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqa1JNU2lEYTJmWktyLTE5cWlYTG1uSi04VkluZ3xBQ3Jtc0tuTEwyY3VzWkVFWlN2UGxYX3FQeXRnVGRHUWp3SEdUY2FBZVUweUNsbzNVb21EdmctQlU1VHJtSUV4N3RUeEtRUVUtNjRyaWtOTVFTOHI3U0l0SElUNjdxZjhRRGNUWWMtdTNyQ2hBeXlteHRnY3hMQQ&q=https%3A%2F%2Fjakevdp.github.io%2FPythonDataScienceHandbook%2Findex.html&v=7q_OJvQQ7vY">https://jakevdp.github.io/PythonDataS...</a> Learn deep learning (pro) ✅ book: <a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbWNtclgwZW53ZjhjWUFFSzYycHdoSDFYMzRtd3xBQ3Jtc0trNWx1TzgtZkVyWElqQm9OTVM4eUR0T0ZSRnRocjJIMDdlbUtuQzB5M0Nodm0zaVR2bjFOWjZVbGF5ckJTZGZMU0x0R2wzVFdpUEt0ck1RRXBZRVFxMEgzZEFqRDBTZDJNVUR3ZG5HSjd6R2dDZzFmWQ&q=https%3A%2F%2Fgithub.com%2Fjanishar%2Fmit-deep-learning-book-pdf&v=7q_OJvQQ7vY">https://github.com/janishar/mit-deep-...</a> (you'll find a good pdf in this GitHub repo) TIME: at least 1 year, more possibly.

STEP5: Get strong mathematical foundations

<ul><li>You may need to read papers before or go back to basics after reading a paper, this is not a linear process.</li><li>This is tough and its gonna suck but learning how to read paper is important for ML engineers and researchers a lot.</li><li>Start reading research papers and implement 1 paper from scratch. You will learn so much.</li><li>use https://arxiv.org/</li></ul>TIME: life long, gets easier with time.

STEP4: Read and implement research papers 

<ul><li>ML is a super useful field.</li><li>Too many resources causes decision fatigue but its really easy to learn it, no matter your background. </li><li>Most courses are reiterating on the same things.</li></ul>

ML and main obstacles to learning it [solved]

We are getting deeper into the mid level of knowledge pyramind for ML learning.Learn ML (middle-level intro) ✅ course: <a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbTY1UkhLY2FhcUhaaWdxM2l2UVFUZXc4dkozQXxBQ3Jtc0tsVXY4aGVUMzBJbGU3NVFtM3dmM0N2eU9CUEFiVkdKNDdsVWJnMEYtSHB5SUlNZ0VWckdOZjZ5VVNIa1ZncTllMWlWaWxsQkFPakJPQUpDazFBSDZxc2p5aXo3RzZNWWN2MDlyMUNaaWhjZXRyMkczNA&q=https%3A%2F%2Fcourse.fast.ai%2F&v=7q_OJvQQ7vY">https://course.fast.ai/</a>✅ course: <a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbDYtbktBamw0WmZVZUJDQVNsdHotYlplemQxZ3xBQ3Jtc0trTVVjb3lzNVZLeURuUzJhb2pTRmRmSXVCeUx6dHFMSXFpbXZ4Q3ZnRXBtQnIyMzhEV1I3R01xa29YTms0MWZuV29uZEZ1emxrNllMa3Fvd3E2MUp3bVpEc0Q3ZHVZT1NRckVtdGZ2dlNFNmNuNVFKaw&q=https%3A%2F%2Fcourse19.fast.ai%2Fpart2&v=7q_OJvQQ7vY">https://course19.fast.ai/part2</a> Again code, code, code. Open-source some projects on GitHub. Focus on one specific DL framework.(PyTorch)TIME : 6 MONTH INCLUDING PRACTICE (MODERATE)

STEP3: Getting deeper (fast.ai)

Learn ML (high-level intro):INPUT MODE -( ingest knowledge that you do not know)✅ course: <a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbWhJQzlURFlxMEdkTDJaM21RM0hRc01GdFYzd3xBQ3Jtc0tuakIzX2NSZXJlVE85bDQtdnJ1SXhqZmlDdEsyOTIzQkxubURxS3djeEptcjVaVXlxaWRveEZ2b2FucmNPS08wOTh3RzEzNGlRQ0NWcHRpUjZsUkRXWXdCWUZiZm1DQ2c4UDVzRVVoRzhLdDYxeE1kdw&q=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fmachine-learning&v=7q_OJvQQ7vY">https://www.coursera.org/learn/machin...</a>✅ course: <a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbElFUWFFX3FBbnNUaU1rZS1OTm9UcFlkUFh0d3xBQ3Jtc0trblZKS0JzTnNmc0FHT1M4X3JGNTFPQ29aMGo2OVFjTGJScUUwV0tEbUVGeTh0dVg0cllRWm1vQldVUVZVa1JxdzBuSHBtQTZ3d2ZaLWQ3YThLVXhyWFJnbHpLX2w4ZVVRcUx1bHB4NXVWdkJvMUp2cw&q=https%3A%2F%2Fwww.coursera.org%2Fspecializations%2Fdeep-learning&v=7q_OJvQQ7vY">https://www.coursera.org/specializati...</a>OUTPUT MODE - + at least 1 open-source project (on github or some website as public artifact)+ 1 blog ( output something practical by structuring your knowledge)TIME : 2 MONTH INCLUDING PRACTICE (INTENSIVE)

STEP2: Get a high-level intro to ML (Coursera)

All the python knowledge you need resources!✅ video: <a href="https://www.youtube.com/watch?v=rfscVS0vtbw&t=0s">https://www.youtube.com/watch?v=rfscV...</a>✅ book: <a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbndQeDVveEJfS3BlS1NtalpwZWMwem9UZy1iQXxBQ3Jtc0tuRURoOE5aaXpHLThkRXBKNnZfNndOb0otMlM4WnZ5dTdXaERPcUowZkNpcDJwS0JQOGQtc1VfTllxZUZEbFEtTmJxMTNQYmVZMGl6Y1hEYnFVUXlCdkxEMThER3owWUZOaVhMVlBwOERVM2hXcHhQcw&q=https%3A%2F%2Fautomatetheboringstuff.com%2F&v=7q_OJvQQ7vY">https://automatetheboringstuff.com/</a>Learn everything else about Python on the fly.use google, stackoveflow, geeksforgeeks.TIME : 1 MONTH INCLUDING PRACTICE (EASY)

STEP1: Learn to code (in Python)

TIP1: Learn how to learn TIP2: Learn only the tools you need TIP3: Get into the output mode (code, blog) TIP4: Focus (the field is too broad) TIP5: Follow AI people on Twitter TIP6: Watch Lex's AI podcastBONUS TIPS: ✅ course: <a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqblBsZmV2TzlvbERBeV9sRWxWQ0h4dURYMEFUZ3xBQ3Jtc0tsX2t3c0NfTmxUNUVBSHhGMGVWNXo3Q0MwQ3YzbHRZX3VTc0lVamdVVDhRN2V3SUd1NGR2M1l6NkxyWDRuZnFJS0haMzFYYmVTZ2JxcXYtclNxOVlHdEdlTjZaaDg4TWpzSjNqbWxYR3dseHJ6enNGQQ&q=https%3A%2F%2Fwww.coursera.org%2Flearn%2Flearning-how-to-learn&v=7q_OJvQQ7vY">https://www.coursera.org/learn/learni...</a> ✅ podcast: <a href="https://www.youtube.com/user/lexfridman">https://www.youtube.com/user/lexfridman</a>✅ Twitter the people I follow: <a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqa2o3YTN1S01jeUNpVG9GaTBzX0xvSXhER0c2QXxBQ3Jtc0tuZDA4ZUs2Z0RwSEJhMVdUUFdJS1YwMkNEeHdjQkt6M0h5V0dXSUpRQngyeWFPc3dNb2sybEZlZmphVF9GNnd2X3E3d0xFZzE0V1R6VGxJZ21DODNtQm5OcEpQN00yQnNpS25rNWtwSnFkb09lQUVOOA&q=https%3A%2F%2Ftwitter.com%2Fgordic_aleksa&v=7q_OJvQQ7vY">https://twitter.com/gordic_aleksa</a> ✅ My GitHub: <a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbmQ2QzRRd1hyZnE3RFBIZmoyR1NfbkZ2RHNvd3xBQ3Jtc0tuLVpXX3dSbmhiVW5PMGRuTkVVOF9sQVB1eWJlNFNXR0RGbkFTOWlWOWY1a243a0U2bzdlXzZRT2VkNXU3b2E0TzU0Vm5qU3BsTHVtbzllZFBCTUFxcEl5N1IyTHpTbUV0MFB2UjVtdTczNjdVQkp5OA&q=https%3A%2F%2Fgithub.com%2Fgordicaleksa&v=7q_OJvQQ7vY">https://github.com/gordicaleksa</a>

BONUS TIPS

I find machine learning to be the most satisfying education for everybody who has passed through the ordeals of learning it.

❤️ Become The AI Epiphany Patreon ❤️ ► https://www.patreon.com/theaiepiphany ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Bunch of you asked me how to get started in machine learning. So I thought I should make a video about it. List of resources: ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Learn Python ✅ video: https://www.youtube.com/watch?v=rfscVS0vtbw ✅ book: https://automatetheboringstuff.com/ Learn everything else about Python on the fly. Learn ML (high-level intro) ✅ course: https://www.coursera.org/learn/machine-learning ✅ course: https://www.coursera.org/specializations/deep-learning + at least 1 open-source project + 1 blog Learn ML (middle-level intro) ✅ course: https://course.fast.ai/ ✅ course: https://course19.fast.ai/part2 Again code, code, code. Open-source on GitHub. Start reading research papers and implement 1 paper from scratch. Learn ML (pro) ✅ MML book: https://mml-book.github.io/book/mml-book.pdf Supplements: ✅ 3B1B LA: https://www.youtube.com/watch?v=fNk_zzaMoSs&list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab ✅ 3B1B Calculus: https://www.youtube.com/watch?v=WUvTyaaNkzM&list=PLZHQObOWTQDMsr9K-rj53DwVRMYO3t5Yr ✅ chapter 5: https://jakevdp.github.io/PythonDataScienceHandbook/index.html Learn deep learning (pro) ✅ book: https://github.com/janishar/mit-deep-learning-book-pdf (you'll find a good pdf in this GitHub repo) BONUS TIPS: ✅ course: https://www.coursera.org/learn/learning-how-to-learn ✅ podcast: https://www.youtube.com/user/lexfridman ✅ Twitter the people I follow: https://twitter.com/gordic_aleksa ✅ My GitHub: https://github.com/gordicaleksa ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ ⌚️ Timetable: 0:00 ML and main obstacles to learning it 1:50 STEP1: Learn to code (in Python) 3:36 STEP2: Get a high-level intro to ML (Coursera) 4:43 How much time do I need to complete it? 5:05 Code your own project (GitHub, Medium) 6:53 STEP3: Getting deeper (fast.ai) 8:26 STEP4: Read and implement research papers 10:00 STEP5: Get strong mathematical foundations 11:35 TIP1: Learn how to learn 12:04 TIP2: Learn only the tools you need 12:38 TIP3: Get into the output mode (code, blog) 12:58 TIP4: Focus (the field is too broad) 13:24 TIP5: Follow AI people on Twitter 13:37 TIP6: Watch Lex's AI podcast 13:52 Comment and subscribe ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 💰 BECOME A PATREON OF THE AI EPIPHANY ❤️ If these videos, GitHub projects, and blogs help you, consider helping me out by supporting me on Patreon! The AI Epiphany ► https://www.patreon.com/theaiepiphany One-time donation: https://www.paypal.com/paypalme/theaiepiphany Much love! ❤️ ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 💡 The AI Epiphany is a channel dedicated to simplifying the field of AI using creative visualizations and in general, a stronger focus on geometrical and visual intuition, rather than the algebraic and numerical "intuition". ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 👋 CONNECT WITH ME ON SOCIAL LinkedIn ► https://www.linkedin.com/in/aleksagordic/ Twitter ► https://twitter.com/gordic_aleksa Instagram ► https://www.instagram.com/aiepiphany/ Facebook ► https://www.facebook.com/aiepiphany/ 👨‍👩‍👧‍👦 JOIN OUR DISCORD COMMUNITY: Discord ► https://discord.gg/peBrCpheKE 📢 SUBSCRIBE TO MY MONTHLY AI NEWSLETTER: Substack ► https://aiepiphany.substack.com/ 💻 FOLLOW ME ON GITHUB FOR COOL PROJECTS: GitHub ► https://github.com/gordicaleksa 📚 FOLLOW ME ON MEDIUM: Medium ► https://gordicaleksa.medium.com/ ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ #machinelearning #learnmachinelearning #deeplearning

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Bunch of you asked me how to get started in machine learning.
So I thought I should make a video about it.

List of resources:
▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 
Learn Python
✅ video: https://www.youtube.com/watch?v=rfscVS0vtbw
✅ book: https://automatetheboringstuff.com/
Learn everything else about Python on the fly.

Learn ML (high-level intro)
✅ course: https://www.coursera.org/learn/machine-learning
✅ course: https://www.coursera.org/specializations/deep-learning
+ at least 1 open-source project + 1 blog

Learn ML (middle-level intro)
✅ course: https://course.fast.ai/
✅ course: https://course19.fast.ai/part2
Again code, code, code. Open-source on GitHub.

Start reading research papers and implement 1 paper from scratch.

Learn ML (pro)
✅ MML book: https://mml-book.github.io/book/mml-book.pdf
Supplements:
✅ 3B1B LA: https://www.youtube.com/watch?v=fNk_zzaMoSs&list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab
✅ 3B1B Calculus: https://www.youtube.com/watch?v=WUvTyaaNkzM&list=PLZHQObOWTQDMsr9K-rj53DwVRMYO3t5Yr
✅ chapter 5: https://jakevdp.github.io/PythonDataScienceHandbook/index.html

Learn deep learning (pro)
✅ book: https://github.com/janishar/mit-deep-learning-book-pdf
(you'll find a good pdf in this GitHub repo)

BONUS TIPS:
✅ course: https://www.coursera.org/learn/learning-how-to-learn
✅ podcast: https://www.youtube.com/user/lexfridman
✅ Twitter the people I follow: https://twitter.com/gordic_aleksa

✅ My GitHub: https://github.com/gordicaleksa
▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 

⌚️ Timetable: 
0:00 ML and main obstacles to learning it
1:50 STEP1: Learn to code (in Python)
3:36 STEP2: Get a high-level intro to ML (Coursera)
4:43 How much time do I need to complete it?
5:05 Code your own project (GitHub, Medium)
6:53 STEP3: Getting deeper (fast.ai)
8:26 STEP4: Read and implement research papers 
10:00 STEP5: Get strong mathematical foundations
11:35 TIP1: Learn how to learn
12:04 TIP2: Learn only the tools you need
12:38 TIP3: Get into the output mode (code, blog)
12:58 TIP4: Focus (the field is too broad)
13:24 TIP5: Follow AI people on Twitter
13:37 TIP6: Watch Lex's AI podcast
13:52 Comment and subscribe 

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💰 BECOME A PATREON OF THE AI EPIPHANY ❤️ 

If these videos, GitHub projects, and blogs help you,
consider helping me out by supporting me on Patreon! 

The AI Epiphany ► https://www.patreon.com/theaiepiphany
One-time donation: https://www.paypal.com/paypalme/theaiepiphany 

Much love! ❤️

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💡 The AI Epiphany is a channel dedicated to simplifying the field of AI using creative visualizations and in general, a stronger focus on geometrical and visual intuition, rather than the algebraic and numerical "intuition". 

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LinkedIn ► https://www.linkedin.com/in/aleksagordic/ 
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📢 SUBSCRIBE TO MY MONTHLY AI NEWSLETTER:
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💻 FOLLOW ME ON GITHUB FOR COOL PROJECTS: 
GitHub ► https://github.com/gordicaleksa 

📚 FOLLOW ME ON MEDIUM:
Medium ► https://gordicaleksa.medium.com/
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#machinelearning #learnmachinelearning #deeplearning

x-Google DeepMind, x-Microsoft engineer explaining AI. ❤️ 

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💰 BECOME A PATREON OF THE AI EPIPHANY ❤️ 

If my YouTube videos, GitHub projects, and blogs help you,
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One-time donation - https://www.paypal.com/paypalme/theaiepiphany 


STEP1: Learn to code (in Python)

Similar ideas to STEP1: Learn to code (in Python)

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Get organized

Pay attention in class

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