20_conclusion.ipynb

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    "# Concluding Thoughts"
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    "Congratulations! You've made it! If you have worked through all of the notebooks to this point, then you have joined a small, but growing group of people that are able to harness the power of deep learning to solve real problems. You may not feel that way; in fact you probably do not feel that way. We have seen again and again that students that complete the fast.ai courses dramatically underestimate how effective they are as deep learning practitioners. We've also seen that these people are often underestimated by those that have come out of a classic academic background. So for you to rise above your own expectations and the expectations of others what you do next, after closing this book, is even more important than what you've done to get to this point.\n",
    "\n",
    "The most important thing is to keep the momentum going. In fact, as you know from your study of optimisers, momentum is something which can build upon itself! So think about what it is you can do now to maintain and accelerate your deep learning journey. <<do_next>> can give you a few ideas."
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    "We've talked a lot in this book about the value of writing, whether it be code or prose. But perhaps you haven't quite written as much as you had hoped so far. That's okay! Now is a great chance to turn that around. You have a lot to say, at this point. Perhaps you have tried some experiments on a dataset which other people don't seem to have looked at in quite the same way — so tell the world about it! Or perhaps you are just curious to try out some ideas that you had been thinking about while you were reading; now is a great chance to turn those ideas into code.\n",
    "\n",
    "One fairly low-key place for your writing is the fast.ai forums at forums.fast.ai. You will find that the community there is very supportive and helpful, so please do drop by and let us know what you've been up to. Or see if you can answer a few questions for those folks who are earlier in their journey than you.\n",
    "\n",
    "And if you do have some success, big or small, in your deep learning journey, be sure to let us know! It's especially helpful if you post about it on the forums, because for others to learn about the successes of other students can be extremely motivating.\n",
    "\n",
    "Perhaps the most important approach for many people to stay connected with their learning journey is to build a community around it. For instance, you could try to set up a small deep learning Meetup in your local neighbourhood, or a study group, or even offer to do a talk at a local meet up about what you've learned so far, or some particular aspect that interested you. It is okay that you are not the world's leading expert just yet – the important thing to remember is that you now know about plenty of stuff that other people don't, so they are very likely to appreciate your perspective.\n",
    "\n",
    "Another community event which many people find useful is a regular book club or paper reading club. You might find that there are some in your neighbourhood already, or otherwise you could try to get one started yourself. Even if there is just one other person doing it with you, it will help give you the support and encouragement to get going.\n",
    "\n",
    "If you are not in a geography where it's easy to get together with like-minded folks in person, drop by the forums, because there are lots of people always starting up virtual study groups. These generally involve a bunch of people getting together over video chat once every week or so, and discussing some deep learning topic.\n",
    "\n",
    "Hopefully, by this point, you have a few little projects that you put together, and experiments that you've run. Our recommendation is generally to pick one of these and make it as good as you can. Really polish it up into the best piece of work that you can — something you are really proud of. This will force you to go much deeper into a topic, which will really test out your understanding, and give you the opportunity to see what you can do when you really put your mind to it.\n",
    "\n",
    "Also, you may want to take a look at the fast.ai free online course which covers the same material as this book. Sometimes, seeing the same material in two different ways, can really help to crystallise the ideas. In fact, human learning researchers have found that this is one of the best ways to learn material — to see the same thing from different angles, described in different ways.\n",
    "\n",
    "Your final mission, should you choose to accept it, is to take this book, and give it to somebody that you know — and let somebody else start their way down their own deep learning journey!"
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