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R - File IO

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Introduction R deals with data. So it has functions for various aspects of data processing. Reading from in input file is a very important aspect of data processing. R provides functions for reading and writing data to various file formats. File Dump R allows you to dump data into a file. Such file can be read only in R > df = mtcars > save(file = "file.out", compress = T, list = c("df")) > This saves the contents of df into file.out. The same can be loaded back from the file using the load method > load(file = "file.out") > head(df, 3) mpg cyl disp hp drat wt qsec vs am gear carb Mazda RX4 21.061601103.902.62016.460144 Mazda RX4 Wag 21.061601103.902.87517.020144 Datsun 71022.84108933.852.32018.611141 > Note the parameter compress=T . Obviously this results in a compressed output file. If you check out the generated file, it is an illegible binary file. You have an option to use ascii=T, that generates a file with…

Recurrent Neural Networks

Convolutional Neural Networks

Introduction to Chatbots

Introduction to Image Processing

Introduction to Natural Language Processing

Introduction to Keras

Introduction to TensorFlow

Introduction to Pandas

Introduction to SciKit Learn

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Introduction SciKitLearn is a library has a chunk of ready implementations of most basic Machine Learning algorithms. Machine Learning implementation gets absolutely quite simple when you use SciKitLearn. Most of the algorithms have ready configurable classes that you just instantiate and then "fit" the model to the training data and then verify with the test data. Implementation It provides for most of the scenarios and algorithms. Below are some typical usages of the common ones. Nearest NeighborsLogistic RegressionDecision TreesRandom ForestsSupport Vector MachinesNeural Networks This should be enough to give you a flavor of what you can expect in ScikitLearn. Ofcourse it provides a lot more than this. Reference The API Reference and the Tutorials on the ScikitLearn website provide a good detail if you want to read further. If you like books, you can check this out

Neural Networks & Deep Learning

Logistic Regression

Reinforcement Learning

Introduction to Unsupervised Learning & Clustering

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Introduction Unsupervised learning, as the name suggests, is about learning without supervision. What does it mean to learn without supervision? What can you learn without supervision? As we saw in the regression, the supervision comes from a part of the input data set - that is required to ascertain the correctness of your hypothesis. The input data has the questions as well as correct answers - the machine just needs to map them. Unsupervised learning is quite different from this. Here, we do not have any answers. No questions either! Then what do we have? We have raw data and we have no idea about its structure. There is nothing we can learn from it - "from" implies supervision. Unsupervised learning is just making sense of the data in hand. This is not just a theoretical fantacy. Unsupervised learning has a great application for analyzing data that we know nothing about. When faced with such a situation, of huge chunk of unknown data, that natural tendency is to categor…

R - Lists

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Introduction Lists are the objects which contain elements of different types like numbers, strings, vectors, data frames and another list inside it. A list can also contain a matrix or even function as its elements. List is created using list() function. Lists are typically used for organizing data rather than processing it. Creating a List Lists are created using the list() function. Following is an example to create a list containing strings, numbers, vectors and a logical values. # Create a list containing strings, numbers, vectors and a logical# values. > list_data <- list(mtcars[1:5,], c('A', 'Sample', 'Vector'), c(21,32,11), TRUE, 51.23, 119.1) > list_data [[1]] mpg cyl disp hp drat wt qsec vs am gear carb Mazda RX4 21.061601103.902.62016.460144 Mazda RX4 Wag 21.061601103.902.87517.020144 Datsun 71022.84108933.852.32018.611141 Hornet 4 Drive 21.462581103.083.21519.441031 Hornet Sportabout 18.783601753.153.44…