Machine learning is the process of teaching a computer system how to make an accurate prediction of the fetched data. It is one of the fastest-growing fields of the era.
Everything changes so fast with the help of machine learning algorithms that if we don’t learn this cool stuff now then we might have to chase these in the future.
Almost all giant organizations are taking the benefit of machine learning and continuously looking for changes to become more efficient in their respective domains. But as I said, machine learning is continuously evolving, so if you’re interested in this, then you should evolve with it. However, we know that it is almost impossible for an individual to remember all of the practices of the algorithms, operations, functions, and formulas of every concept.
That is why we are bringing the top 10 cheat sheets for you.
These cheat sheets will make your work easier enough to understand these complex things in a single shot.
But before giving you these cheat sheets for machine learning, I’d love to talk about machine learning and its few examples.
As we discussed earlier, machine learning is mainly all about predictions. So, it doesn’t matter if you have to choose the colour of a single orange from a basket of mixed fruits or to select the cheapest property according to your preferences, machine learning is helpful in each scenario.
There are a few practical examples that you might be interested in knowing what is happening around you. Yeah, like images recognition(X-Ray, facial recognition), speech recognition(voice search, voice dialling), medical diagnosis(uses to recognize disease like cancer), statistical arbitrage(Trading), predictive
analysis(Transaction legit or not), extraction(Develop different methods to prevent & treat different diseases), and many more.
I have structured these cheat sheets for you in such a good way, you can cover each topic easily. You don’t have to worry about the clarity of the content. This cheat sheet is prepared in such a way that you can easily learn all the required technology to become a pro in machine learning.
Contents
1) Supervised Learning
This is one of the very first cheat sheets created for the Stanford Learning Class. From this cheat sheet, you can easily learn about supervised machine learning in a very concise manner. It covers all of the important topics like supervised learning notations, classification, logistic regression, generative learning, linear regression, general learning theory, naive Bayes, Gaussian discriminant analysis, tree-based, and ensemble methods.
2) Unsupervised Machine Learning
It is also from the class of Stanford Machine learning. You can get a well-structured overview of beginner-friendly f unsupervised machine learning. It gives you a brief of K means clustering, clustering assessment metrics,
Expectation-maximization(EM), Independent and Principal component analysis.
3) Deep Learning
Well, deep learning is something people get tired of understanding but believe me you’ll fall in love with this cheat sheet of machine learning. It covers everything about neutral networks, control, entropy, recurrent and convolutional neural networks, reinforcement learning. However, you can’t learn everything from a single cheat sheet of deep learning. But you can get a quick start with it.
4) Statistics and Probability
You can say it is a refresher for the beginner to learn about statistics and probabilities that can be helpful in the field of machine learning. You can consider it as the best cheat sheet for statistics and probability for machine learning. You can find an introduction to probabilities and combinatorics, conditional probability, parameter estimation, and many other concepts. Worth giving a shot!
5) Tips and Tricks
Well, this portion covers small tips, tricks, and techniques to learn machine learning efficiently and in a better way than the majority of learners. The majority of the learners like to have such things because this kind of cheat sheet will provide you valuable insights from a highly skilled person of the respective domain. And a bonus tip if you’re into data science then it can be a lifesaver for you.
6) Linear Algebra and Calculus
So, fellas! boring stuff for the majority of learners comes into the picture here. But it is fundamentally a very important concept from the perspective of machine learning. A few things covered in this cheat sheet are matrix properties and operations, matrix notation and calculus, etc.
7) Data Science
This cheat sheet is like a diamond for beginners who are just trying to give a fresh shot in the field of data science. But for those who already know beginner-friendly concepts of machine learning and have some experience, you should definitely skip this one. On the other hand, like I said beginners who want to learn Python for data science will love this one.
8) Visual Guide to Neural Network Infrastructure
This cheat sheet will give you a quick introduction to the most commonly used infrastructure of neural networks. There are more than 25 neural network infrastructures in it, which I guess is enough even for a practitioner. These network architectures mainly include Markov chain, Hopfield network, perceptron, feedforward, Boltzmann machine, other things related to deep convolutional networks.
9) Tensorflow
This is one of the most used cheat sheets for TensorFlow, and you can surely go for it. Sometimes, you need TensorFlow in machine learning, this is why I’ve added it in. Give it a look!
10) Machine Learning Test
Now, you all have the resources to learn about machine algorithms. This cheat sheet is well structured and covers almost every algorithm of machine learning.
Like every discussed problem in machine learning like regression, clustering, and classification, and other good collections of stuff.
Everything is covered in these cheat sheets and I’ve tried my best to make it beginner-friendly. Moreover, even intermediate level learners can find it helpful in many places. I’m hoping now after getting such a well structured
cheat sheets, you can ease your journey into machine learning.