Hey Developer, I’m back with a new series of blogposts on the foundation of statistics for data science and machine learning. Here will be covering all the topics that are essential for good understanding of data science and machine learning concepts.
Continue readingHey Developer’s, I’m back with a new topic which is Bayes Theorem in the series of statistics foundations.
Continue readingHey Developer’s, I’m back with a new topic which is Law of Total Probability in the series of statistics foundations.
Continue readingHey Developer’s, I’m back with a new topic which is Multiplicative and Additive Law Of Probability in the series of statistics foundations.
Continue readingHey Developer’s, I’m back with a new topic which is Independence Of Events in the series of statistics foundations.
Continue readingHey Developer’s, I’m back with a new topic which is Conditional and Unconditional Probability in the series of statistics foundations.
Continue readingHey Developer’s, I’m back with a new topic which is Probability of Union Of Events in the series of statistics foundations.
Continue readingHey Developer’s, I’m back with a new topic which is Multinomial Coefficients in the series of statistics foundations.
Continue readingHey Developer’s, I’m back with a new topic which is Binomial Coefficients in the series of statistics foundations.
Continue readingHey Developer’s, I’m back with a new topic which is Combinatorics in the series of statistics foundations.
Continue readingHey Developer’s, I’m back with a new topic which is Permutations in the series of statistics foundations.
Continue readingHey Developer’s, I’m back with a new topic which is Counting Sample Points in the series of statistics foundations.
Continue readingHey Developer’s, I’m back with a new topic which is Discrete and Continuous Probability in the series of statistics foundations.
Continue readingHey Developer’s, I’m back with a new topic which is Rules of Probability in the series of statistics foundations.
Continue readingHey Developer’s, I’m back with a new topic which is Introduction To Probability and Examples in the series of statistics foundations.
Continue readingHey Developer’s, I’m back with a new topic which is Independence Of Events in the series of statistics foundations.
Continue readingHey Developer’s, I’m back with a new topic which is Set Operations On Events in the series of statistics foundations.
Continue readingHey Developer’s, I’m back with a new topic which is Experiments, Events, Sample Spaces & Points in the series of statistics foundations.
Continue readingHey Developer’s, I’m back with a new topic which is Cardinality, Set Complement and Set Laws in the series of statistics foundations.
Continue readingHey Developer’s, I’m back with a new topic which is a Sets Membership in the series of statistics foundations.
Continue readingHey Developer’s, I’m back with a new topic which is an introduction to sets in the series of statistics foundations.
Continue readingDecision Tree is a type of Supervised Learning Algorithm wherein the data is continuously split on the basis of certain parameters. To understand the decision tree in a better way let’s take an example
Continue readingDecision Tree is a type of Supervised Learning Algorithm wherein the data is continuously split on the basis of certain parameters. To understand the decision tree in a better way let’s take an example
Continue readingCloud Computing is the delivery of IT resources over the internet. The cloud is like a virtual data center accessible via the internet that allows you to manage.
Continue readingGoogle has inked a deal with India’s third-largest telecom operator as the American giant looks to grow its cloud customer base in the key overseas market that is increasingly emerging as a new cloud battleground for AWS and Microsoft .
Continue readingThat list is great for checking whether a particular programming language is in use today. However, if you’re new to programming, I don’t recommend choosing a language solely based on a list.
Continue readingMachine learning resources containing Deep Learning, Machine Learning and Artificial Intelligent resources. A-Z Machine learning resources to learn machine learning.
Continue readingAffine Transformation helps to modify the geometric structure of the image, preserving parallelism of lines but not the lengths and angles. It preserves collinearity and ratios of distances. It is one type of method we can use in Machine Learning and Deep Learning for Image Processing and also for Image Augmentation.
Continue readingAI, ML and DL are related to each other. AI is a superset of ML and DL. What we do in the field of ML and DL all comes under AI. To better understand all of them, Let’s dive in…
Continue readingA hyperparameter is a parameter or a variable we need to set before applying a machine learning algorithm into a dataset.These parameters express “High Level” properties of the model such as its complexity or how fast it should learn. Hyperparameters are usually fixed before the actual training process begins.
Continue readingIn this notebook we will be learning how to use Transfer Learning to create the powerful convolutional neural network with a very little effort, with the help of MobileNetV2 developed by Google that has been trained on large dataset of images.
Continue readingTraining error should steadily decrease, steeply at first, and should eventually plateau as training converges.If the training has not converged, try running it for longer.
Continue readingIn the real world, it is very difficult to explain behavior as a function of only one variable, and economics is no different.
Continue readingEver wonder why sometimes attributes, methods in Python start with single underscore, double underscore(“dunder”), end with single underscore etc. Single…
Continue readingA high order function is a function that operates on other functions, either by taking a function as it argument…
Continue readingPython’s zip() function creates an iterator that will aggregate elements from two or more iterables. zip() maps the similar index…
Continue readingDeep Learning is a subfield of Machine Learning because it makes use of Deep Neural Networks inspired by the structure and function of the brain called Artificial Neural Networks.
Continue readingRegression is basically a statistical approach of finding a relationship between the variables. Linear regression is one type of regression we use in Machine Learning.
Continue readingHere are 15 Best Machine Learning Course for Machine Learning. It will give you the great knowledge about Machine Learning and Deep Learning.
Continue readingWe all love to see beautiful images, but have you ever thought how do computers see an image? In this tutorial, we will give an explanation of how images are stored in a computer.
Continue readingCNN’s achieve state of the art results in the variety of problem areas including Voice User Interfaces, Natural Language Processing, and Computer Vision.
Continue readingTensorFlow the massive open-source platform to develop large scale AI and Deep Learning Models has recently been updated to its newer form TensorFlow 2.0.
Continue readingThough there are various fields out there which requires a laptop with good specifications and you can get it at an affordable price but that’s not the same case for deep learning.
Continue readingMachine Learning today is one of the most sought-after skills in the market. Here are some of the best books which you can use to learn Machine Learning.
Continue readingThe NumPy library is the core library for scientific computing in Python. It provides a high-performance multidimensional array object, and tools for working with these arrays.
Continue readingTextual data in Python is handled with str objects. Since default handling of Text in Python2 and Python3 is different,…
Continue readingA function is a block of code that takes input(s), performs some computation and returns a result. Syntax to create…
Continue readingTuple is a data structure in Python which is an immutable , ordered collection of objects. Tuples are faster and…
Continue readingA Set in Python is a data structure that contains an un-ordered collection of distinct objects. A set in python…
Continue readingA dictionary is an un-ordered data structure, its elements are stored as a key:value pair.Key must be unique and immutableIf…
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