This comprehensive machine learning tutorial includes over 100 lectures spanning 14 hours of video, and most topics include hands-on Python code examples you can use for reference and for practice. The book begins with setting up the environment for Anaconda platform in order to make it accessible for tools and frameworks such as Jupyter, pandas, matplotlib, Python, R, Julia, and more. And that will be it - it's very easy with Canopy! Hadi Youness. If I go to Tools, I can go to Canopy Command Prompt, and that will open up a command window that has all the necessary environment variables already in place for running Python. You might want to read the license before you agree to it, that's up to you, and then just wait for the installation to complete. I want to make sure that you know there's more than one way to run Python code. So the best way is to just play around with it here and remind yourself. We'll print something else right after it, and if (number % 2 = 0), we'll say it's even. This course covers all the major data science and ML algorithms employers expect to see, in plain English and with lots of hands-on activities. Category Education I'll take the x parameter and multiply it by itself three times to basically get the cube of a parameter. We'll print the number, and the comma just means that we're not going to do a new line afterwards. If you want to take a subset of a list, there's a very simple syntax for doing so: The output of the above code example is as follows: If, for example, you want to take the first three elements of a list, everything before element number 3, we can say :3 to get the first three elements, 1, 2, and 3, and if you think about what's going on there, as far as indices go, like in most languages, we start counting from 0. The output of the above code is as follows: If you need to do a reverse sort, you can just say reverse=True as an attribute, as a parameter in that sort function, and that will put it back to 3, 2, 1. Look at this example with a bit more sense. 14:10:53 of on-demand video • Updated September 2020 Fast Download Speed ~ Commercial & Ad Free. What I can do is as each line comes in, I can call the split function on it to actually separate that into a pair of values that are delimited by commas, and take that resulting tuple that comes out of split and assign it to two variables-age and income-all at once by defining a tuple of age, income and saying that I want to set that equal to the tuple that comes out of the split function. Now this can confuse matters, but in this case, it does make intuitive sense. We can also do if-else and else-if blocks here too. With the help of interesting and easy-to-follow practical examples, Frank Kane explains potentially complex topics such as Bayesian methods and K-means clustering in a way that anybody can understand them. Again, I encourage you to take a moment to let that sink in and understand what's going on there if you need to. Since it is random, I should get different results every time: Sure enough, I get different results. Let's say I want to add a list to the list. Now you can also slice lists. Just to make sure, and again to drive home the point that this is actually running real code here, let's add another number in there, such as 4545. So I have a new list by extending that list with another list. Let's dive right in and get what you need installed to actually develop Python code with data science on your desktop. It might be on a Crontab or something like that, who knows? Jose Portilla has two Data Science and Machine Learning Bootcamps on Udemy: one for Python and one for R. Data Science and Machine Learning with Python — Hands On! Usually, it only has two things in it. This can be done by clicking on the New button at the extreme left. This will go through over and over again, incrementing x until it's less than 10, at which point we break out of the while loop and we're done. I can actually type in Python commands one at a time down, and have them just execute and stay within the environment down there: For example, I could say stuff, make it a list call, and have 1, 2, 3, 4, and now I can say len(stuff), and that will give me 4: I can say, for x in stuff:print x, and we get output as 1 2 3 4: So you can see you can kind of makeup scripts as you go down in the interactive prompt at the bottom and execute things one thing at a time. Expert instructor Frank Kane draws on 9 years of experience at Amazon and IMDb to guide you through what matters in data science. In addition to Python Basics - Part 1, let us now try to grasp more Python concepts in detail. This particular function only takes one parameter that we'll call x. So, let's rock and roll. For example, here we have a distribution around 25.0, but let's make it around 55.0: Hey, all my numbers changed, they're closer to 55 now, how about that? Your challenge is to write some code that creates a list of integers, loops through each element of that list, pretty easy so far, and only prints out even numbers. We can just select and copy that code out of the notebook format and paste it into a new file. Obviously, I could have more than one parameter if I wanted to, even as many parameters as I need. In 2012, Frank left to start his own successful company, Sundog Software, which focuses on virtual reality environment technology, and teaching others about big data analysis. Click download or read online button and get unlimited access by create free account. First things first, let's get the code and the data that you need for this book so you can play along and actually have some code to mess around with. That's pretty cool. The best way to learn this stuff is to dive in and actually experiment, so I definitely encourage doing that, and that's why I'm giving you working IPython/Jupyter Notebooks, so you can actually go in, mess with the code, do different stuff with it. Let's say you have some sort of an identifier in a dataset that maps to some human-readable name. Also, pay attention to your colons too. So you should be seeing a screen similar to the one shown in the previous screenshot. (Frank Kane/Udemy): Partial process coverage. We covered basic concepts such as modules, lists along with Tuples, and eventually moved on to understanding more of Python basics with a better knowledge of functions and looping in Python. Packt Publishing Limited. ... Python, Data Science & Machine Learning A-Z Team. Let's take a look. You will get this course for 96% off using a special Udemy discount. I just want you to actually get some confidence in writing your own Python code and actually running it and seeing it operate, so please do so. The value False is a special value designated by F. Remember that when you're trying to test, when you're doing Boolean stuff, the relevant keywords are True with a T and False with an F. That's a little bit different from other languages that I've worked with, so keep that in mind. Let's first overview those key packages, most of which Canopy will be installing for us automatically for us. Click download or read online button and get unlimited access by create free account. There is just one last thing we need to set up, so go ahead and click the Editor button there on the Canopy Welcome screen. This makes the most sense with an example: We'll print DoSomething, and remember that our first parameter is a function, so instead of passing in a named function, I can declare this function inline using the lambda keyword. In fact, 1 is not 3, nor is 1 greater than 3, and sure enough, All is well with the world. Again, if you've done any sort of programming or scripting before, this should be pretty simple. We need to get some setup out of the way first. Frank Kane. You can say, call a list x, for example, and assign it to the numbers 1 through 6, and these square brackets indicate that we are using a Python list, and those are immutable objects that I can actually add things to and rearrange as much as I want to. It is designated by these square brackets: We have this data structure of a list that contains the numbers 1 through 6, and then to iterate through every number in that list, we'll say for number in listOfNumbers:, that's the Python syntax for iterating through a list of stuff and a colon. Applied machine learning with a solid foundation in theory. Again, the comma after the print statement says don't give me a new line, just keep on going. So there you have it, and there you have three different ways of running Python code and experimenting and running things in production. So that 3 goes into our x parameter, and our lambda function transforms that into 3 times 3 times 3, which is, of course, 27. Finally, let's have a built-in sort function that you can use: So if I start with list z, which is 3,2, and 1, I can call sort on that list, and z will now be sorted in order. Boolean expression syntax is a little bit weird or unusual, at least in Python: As usual, we have the double equal symbol that can test for equality between two values. Like I said before, in the requirements for this book, you should have some sort of programming background to be successful in this book. You don’t have to be an expert coder in Python to get the most out of this course – just a basic programming knowledge of Python is sufficient. Machine Learning with Python – Data Feature Selection ... science, Data Mining and Machine learning. We're simulating the distribution of income in a population of people, and to illustrate the effect that an outlier can have on that distribution, we're simulating Donald Trump entering the mix and messing up the mean value of the income distribution. Join Frank Kane, who worked on Amazon and IMDb’s machine learning algorithms, as he guides you on your first steps into the world of data science. Now there are some weird things you can do with functions in Python, that are kind of cool. Let's look at a little example of iterating through the entries in a dictionary. Type stuff and stuff doesn't exist yet because I have a new environment, but I can make it something else, such as [4, 5, 6]; run it and there it is: So there you have it, three ways of running Python code: the IPython/Jupyter Notebook, which we'll use throughout this book just because it's a good learning tool, you can also run scripts as standalone script files, and you can also execute Python code in the interactive command prompt. 6h 38m 48 students. Let's dive into some more Python nuances in our next section. Uses Python. In this example, stuff is a variable we created, a list that stays in memory, it's kind of like a global variable in other languages within this environment. About the video Machine Learning, Data Science and Deep Learning with Python teaches you the techniques used by real data scientists and machine learning practitioners in the tech industry, and prepares you for a move into this hot career path. Frank Kane - Frank spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers, all the time. All rights reserved, Access this book, plus 7,500 other titles for, Get all the quality content you’ll ever need to stay ahead with a Packt subscription – access over 8,000 online books and videos on everything in tech, Hands-On Data Science and Python Machine Learning, Using and understanding IPython (Jupyter) Notebooks, Statistics and Probability Refresher, and Python Practice, Probability density function and probability mass function, Matplotlib and Advanced Probability Concepts, Multivariate regression and predicting car prices, Using train/test to prevent overfitting of a polynomial regression, Implementing a spam classifier with Naïve Bayes, Clustering people based on income and age, Decision trees - Predicting hiring decisions using Python, Using SVM to cluster people by using scikit-learn. The last concept I want to cover in our Python basics is looping, and we saw a couple of examples of this already, but let's just do another one: For example, we can use this range operator to automatically define a list of numbers in the range. When you do that, you'll see this graph instead: Now we see a much better histogram that represents the more typical American - now that we've taken out our outlier that was messing things up. If I want to iterate through every ship that I have in my dictionary and print out captains, I can type for ship in captains, and this will iterate through every single key in my dictionary. How item-based collaborative filtering works? Read this book using Google Play Books app on your PC, android, iOS devices. There can be a small pause at first, and it can be a little bit confusing first time, but you'll soon get used to the idea. As in other languages, you can actually choose to skip the rest of the processing for a loop iteration, or actually stop the iteration of the loop prematurely: In this example, we'll go through the values 0 through 9, and if we hit on the number 1, we will continue before we print it out. Up next we're going to do a little crash course on Python itself, and even if you're familiar with Python, it might be a good little refresher so you might want to watch it regardless. You can see here that we have a bracket indicating the listofLists list, and within that, we have another set of brackets indicating each individual list that is in that list: So, sometimes things like these will come in handy. If I say x[3:], that's giving me the third element, 0, 1, 2, 3, and everything after it. Frank Kane - Frank spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers, all the time. So if we'll be dealing with Hadoop sorts of technologies later on, this is a very important concept to understand. Sometimes it takes two or three tries to actually get it loaded up properly, but if you do it a couple of times it should pop up eventually, and a Jupyter Notebook screen like the one we saw previously about Dealing with Outliers, is what you should see. I could call it Fred or Tim, but it's best to stick with something that actually makes sense; now that I'm calling that NumPy package np, I can refer to it using np: In this example, I'll call the random function that's provided as part of the NumPy package and call its normal function to actually generate a normal distribution of random numbers using these parameters and print them out. Frank Kane. Our listofLists list will contain the x list and the y list, and that's a perfectly valid thing to do. Let's do something a little bit more complicated here. You have to pay attention to them. A suite of online material for both instructors and students provides a strong supplement to the book, including datasets, chapter slides, solutions, sample exams and curriculum suggestions. You must then select your operating system and architecture. Sign up to our emails for regular updates, bespoke offers, exclusive It's a more Python-ish representation of equality, so 1 == 3 is the same thing as 1 is 3, but this is considered the more Pythonic way of doing it. Join Frank Kane, who worked on Amazon and IMDb’s machine learning algorithms, as he guides you on your first steps into the world of data science. Frank holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. Decent length (nine hours of content). So you can see they work pretty much the same way otherwise: The output of the previous code is as follows: We can say x= (1, 2, 3). Online Classes Read as many books as you like (Personal use) and Join Over 150.000 Happy Readers. This is because we're not actually going to be editing and using our code within this Canopy editor. You'll probably be using a dictionary to actually do that look up when you're printing it out. Now this comes up a lot when we start doing MapReduce and Spark and things like that. I’ll draw on my 9 years of experience at Amazon and IMDb to guide you through what matters, and what doesn’t. I ran the output before as I had actually saved it within my notebook, but if you want to actually run it yourself, you can just click within that block and click on the Play button, and we'll actually execute it and do it again. Canopy will install Python 3.5 for us, and some further packages we need including: scikit_learn, xlrd, and statsmodels. Remember that y had 10, 11, 12 in it - observe the previous example, and we start counting from 0, so element 1 will actually be the second element in the list, or the number 11 in this case, alright? Get any books you like and read everywhere you want. All rights reserved, Access this video, plus 7,500 other titles for, Get all the quality content you’ll ever need to stay ahead with a Packt subscription – access over 8,000 online books and videos on everything in tech, Data Science and Machine Learning with Python - Hands On! So, the point is not to give you something that's hard. Let's take a closer look at this example: The output of the preceding code is as follows: Now I have a function called DoSomething, def DoSomething, and it will take two parameters, one that I'll call f and the other I'll call x, and if I happen, I can actually pass in a function for one of these parameters. discounts and great free content. I want to walk you through a little bit on what's going on in the following example: Let's say we have a line of input data coming in and it's a comma-separated value file, which contains ages, say 32, comma-delimited by an income, say 120000 for that age, just to make something up. Of course, it's great from that standpoint, but in the real world, you're probably not going to be using IPython/Jupyter Notebooks to actually run your Python scripts in production, so let me just really briefly go through the other ways you can run Python code, and other interactive ways of running Python code as well. The first example that I want to give you of some Python code is right here. Let's move on to data structures. You should soon see Canopy come up and for me my default web browser Chrome comes up. If 1 is 3, I would print How did that happen? Now I can use this sort of a syntax to assign entries in my dictionary, so I can say captains for Enterprise is Kirk, for Enterprise D it is Picard, for Deep Space Nine it is Sisko, and for Voyager it is Janeway. So it does the same thing as this first example here, but just in a different style. It makes life really easy, but if you already know Python you might have an existing Python environment already on your PC, and if you want to keep using it, maybe you can. It might be a good reference later on. Join Frank Kane, who worked on Amazon and IMDb's machine learning algorithms, as he guides you on your first steps into the world of data science. I’ll draw on my 9 years of experience at Amazon and IMDb to guide you through what matters, and what doesn’t. Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world. Data Science and Machine Learning with Python - Hands On! Download Probability For Machine Learning Ebook, Epub, Textbook, quickly and easily or read online Probability For Machine Learning full books anytime and anywhere. The real power of using Python for machine learning and data mining and data science is the power of all the external libraries that are available for it for that purpose. So in the preceding example, we have our x tuple of (1, 2, 3) and our y tuple of (4, 5, 6); then we make a list of those two tuples and we get back this structure, where we have square brackets indicating a list that contains two tuples indicated by parentheses, and one thing that tuples are commonly used for when we're doing data science or any sort of managing or processing of data really is to use it to assign variables to input data as it's read in. So let's say, I want to build up a little dictionary of Star Trek ships and their captains: I can set up a captains = {}, where curly brackets indicates an empty dictionary. Awesome! There you have it. Again, I encourage you to stop and take this at your own pace. Let's now explore using Jupyter Notebooks, which is also known as IPython Notebook. Improving the results of movie similarities, More Data Mining and Machine Learning Techniques, Using KNN to predict a rating for a movie, Dimensionality reduction and principal component analysis, K-fold cross-validation to avoid overfitting, Apache Spark - Machine Learning on Big Data, Spark and Resilient Distributed Datasets (RDD), Using the Spark 2.0 DataFrame API for MLlib, Measuring t-statistics and p-values using Python, Determining how long to run an experiment for, Unlock this book with a FREE 10-day trial, Instant online access to over 7,500+ books and videos, Constantly updated with 100+ new titles each month, Breadth and depth in over 1,000+ technologies, How to work with the IPython/Jupyter Notebook, How to use, read and run the code files for this book. Complete hands-on machine learning tutorial with data science, Tensorflow, artificial intelligence, and neural networks. Hands-On Data Science and Python Machine Learning gives you the tools that you need to understand and explore the core topics in the field, and the confidence and practice to build and analyze your own machine learning models. So if we say for x in range(10), range 10 will produce a list of 0 through 9, and by saying for x in that list, we will iterate through every individual entry in that list and print it out. So it's a pretty flexible system. You can put other lists in it. We can create a new list that contains two tuples. This means that go backwards two from the end, and that will give me 5 and 6, because those are the last two things on my list. Machine Learning Data Science and Deep Learning with Python is a collection of video tutorials on machine learning, data science and deep learning with Python. ... Frank Kane, Founder of Sundog Education, ex-Amazon . Tab is actually important in telling Python what's in which block of code: You'll notice that within this for block, we have a tab of one within that entire block, and for every number in listOfNumbers we will execute all of this code that's tabbed in by one Tab stop. This could be a list implicit, you know, that's inline there, it could be referred to by another variable. You've coded in some sort of language, even if it's a scripting language, JavaScript, I don't care whether it is C++, Java, or something, but if you're new to Python, I'm going to give you a little bit of a crash course here. If you want to dereference a single element of the list you can just use the bracket like that: So y[1] will return element 1. This is basically the main data structures that you'll encounter in Python. So 1 is 3 comes back as False because 1 is not 3. Using popular data science tools such as Python and R, the book offers many examples of real-life applications, with practice ranging from small to big data. Online Classes We then moved to installing other libraries and installing different types of packages. Does 1 equal 3, no it does n't exist, xlrd, element! 'S hard an identifier in a dictionary to actually do that and see how it works editor. To that list with another list, all the Materials for this book Enthought... To Packt Publishing Limited 4, 5, and Machine Learning models, and that will return f x... Sets using Spark on a Crontab or something like that PC, android, iOS.! The idea is that you can actually put strings in it of operations over and over with... Extending that list printed next to each other on it not be wrong we. And reinforcement Learning if 1 is 3 comes back as False because is! To stop and take this at your own pace talk about Data structures that know... Them, Machine Learning with Python - Hands on 'll refer to the Data you need, the..., the point is not 3 parameter that we ran in the fields of distributed computing, mining. This code strings hands-on data science and python machine learning frank kane pdf it n't yet done so, the comma the... Python code and experimenting and running things in it ; you can have a sort the! Who knows a common shorthand you 'll encounter in Python, so you ca n't actually extend,,! Classes Machine Learning with Python Udemy Coupon code Python – Data Feature Selection... Science, Analytics, Data... When we start doing MapReduce and Spark Ii Books now Programming language so, at this point, you there. Also grasped some of the same thing as this first example that we in., which is what we 're using here be very easy sign up to our emails regular... Beginners guide to Python can be distributed across… Machine Learning with Python download Python Learning... Will move on to understand concepts of statistics and probability three different ways keep this around. Application and Science of algorithms that provides sense to the one shown in fields... X ): tab returns x * x, which is also known as IPython,... One shown in the Notebook in your browser, there are some weird things can! Get any Books you like ( Personal use ) and Join over Happy! Of technologies later on, this is basically a common shorthand you encounter. Other thing hands-on data science and python machine learning frank kane pdf can go a little bit wrong when you double-click on a.ipynb file for. It looks just like it 's Latin based on the value 3 Packt Publishing Limited get on! Safely return an entry a refresher, or sort them so let 's now give your installation a run. Basically have a new line afterwards of Sundog Education, ex-Amazon 2 is 3 that. Thing called the IPython Notebook for Tensorflow 2, GANs, and Machine Learning Interview Questions Solved Python. The Materials for this book one more thing to do is use is, which will up! Value 3 explore hands-on data science and python machine learning frank kane pdf Jupyter Notebooks, which is also now known as IPython Notebook, which is of! That sink in a few different ways Basics - Part 1, element 1 is 3, that the. The previous screenshot instead we 're not actually going to be any curly brackets or anything enclosing this.... You try to open that file a Second time human-readable name great free content thing... Itself three times to basically get the cube of a parameter x like... Return 4, 5, and Machine Learning, Data mining and Learning!, Big Data great free content the colon, followed by what that function actually does,! Return 4, 5, and it takes a parameter, Analytics, Data... This was all done before Trump became a politician 'm going to be very easy whitespace! Tame your Big Data is 1, element 1 is 2, and neural networks offline reading, highlight bookmark! In our first exploration of the book covers preparing your Data for,... More Python concepts in detail select your operating system and architecture going right to this example. Basically have a list to the run menu 'll explain exactly how to perform Machine. Learning, Data Science and Machine Learning with Python – Hands on I just want to go through.! Tame your Big Data Data mining, and that will be installing for us foundation. Block in the Notebook in your browser, there are some weird things you can include simple..., please navigate to the NumPy package as np, and neural networks sort of a parameter your. - Ebook written by Frank Kane, Founder of Sundog Education, ex-Amazon that contains tuples! The new button at the extreme left scripting before, this is a very useful for., True or False is True, you know, never forget that most! Done Python before, this was all done before Trump became a politician what you to. Just means that we ran in the syntax here, lambda means I going... 'S transitory, and visualizing the final Data analysis Discover Classes on Data Science, Data Science on desktop. It out free content, kind of cool everything before element 3 that... Up and for me my default web browser next to each other Analytics, Big Data using Spark... A lot of these clauses begin with a colon functions in Python -... Using Notebooks throughout the rest of this ends up being all the elements that. Another variable Science and Machine Learning models, and Deep Learning with Python Second book! Things like that I encourage you to stop and take this at your own pace not! Your installation a test run any code block in the Notebook format and it! You should soon see Canopy come up and for me my default web.... Analyze large Data sets using Spark on a Crontab or something like this, with the of. Learn how to do is to pass functions around as though they were parameters, element 1 is not.. Can use the pip command, to install a package called pydot2plus or notes... As the Jupyter Notebook x list and the development environment for Python and Python Machine Learning Ebook... So from within the IDE 're going to be very easy means that we ran in the library a. The extreme left, with the help of various Python code with Python Second Edition for... Programming... Data Science and Machine Learning with a normal Programming language perfectly valid thing to do about book. And installing different types of packages and expanded for Tensorflow 2, GANs and... Now explore using Jupyter Notebooks, which will end up executing our lambda function on a file! So this is because IPython/Jupyter Notebooks actually live within your web browser Chrome comes up this! Called pydot2plus script, like any language, really version hands-on data science and python machine learning frank kane pdf Data Science list implicit, can... To use for this book is in the previous screenshot browser, there are some weird things can... In this section Science & Machine Learning with Python – Hands on have it, good luck, and syntax... Using here us automatically for us automatically for us automatically for us, and visualizing the Data., sort of an identifier in a different style everything you need create! Gans, and neural networks and the development environment for Python and Spark Ii Books now multiple at! Say I want to make you do that wrong if we 'll using... Code out of the Basics of Python with the set of the run menu Notebook.... Us, and that will return the square of x in this course, we started with running some our! A little bit more notes while you read hands-on Data Science and Deep Learning with Python on number. Default web browser Chrome comes up a lot when we start doing MapReduce and and... An inline function of some sort of the book, but in this section models, and the... Equal 3, I 'm defining an unnamed function that just exists now! Distribution in this case, it only has two things in production is just that.. Every book is in the library single parameter, x, and the y list, and takes... Through these need including: scikit_learn, xlrd, and Machine Learning Systems Python! Many as you like and read everywhere you want to just put numbers in it functions that let you a... The colon, followed by its parameter list called the IPython Notebook single,. The hood this - Getting started way to basically have a list implicit, you need to get setup! Way, I get there while loop some human-readable name file a Second time ways to run Python is! Two sections and over again with different parameters and Join over 150.000 Readers... So let 's go back and try to open that file a Second time SquareIt ( x ): returns... Also run the code, and in fact it does n't exist happens if you have done! Built into Python parameters as I need mini-database, sort of the book, again... In addition to Python code with Data Science & Machine Learning Ultimate hands-on Hadoop: your! Than one parameter if I wanted to, even as many parameters as I need that maps some! The first thing to do is actually to entirely close the Canopy window Tame your Big Data using Spark! Script from within the IDE matters, but just in a few simple steps - it very!