# Law of Total Probability – Statistics Part 19

Hey 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 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 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 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 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 readingHey 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 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 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 readingTensorFlow is a free and open-source software library for dataflow and differentiable programming across a range of tasks. It is a symbolic math library and is also used for machine learning applications such as neural networks.

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 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 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 readingFoundation is the basement for a healthy home. So here comes with the languages too which acts like a foundation…

Continue readingBefore, to train an AI model that can recognize whatever you want it to recognize in pictures, involves lots of expertise in Applied Mathematics and use Deep Learning Libraries. To write the code for the algorithm and fit the code to your images involves lots of time and stress.

Continue readingThe art and science of :

Giving Computers the ability to learn,

To make decisions from data,

Without being explicitly programmed .

Here goes the learning path to become an expert in machine learning.Learn any programming language (Python is highly preferable)

Continue readingIntroduction to Tensorflow the core open source library to help you develop and train ML models.

Continue readingToday,Python is a trending language in the industry and it replaced many of the other programming languages.Machine Learning got easier in Python than from any other language. Whether it is Machine learning or Artificial Intelligence or Data Science it is fun doing with Python.

Continue readingEvery ML project starts with knowing what your data is all about.You should analyze and understand your data and should think of what Algorithms we should choose.

Continue readingIn Todays era people want automation in their life.People want everything on the tip of their finger.People do not care about money they only care about advancement in their life.They want to adapt technology trendz.

Continue readingOur main goal is to prepare people for trending technologies like Cloud, Machine Learning. We make Technology based and Educations based videos.

Continue readingThere are some basic steps involved to develop a machine learning application. I will guide with the basic 7 steps to get started with a machine learning application.

Continue reading“AI is any technology that enables a system to demonstrate human-like intelligence”. “Machine Learning is one type of AI that uses mathematical models trained on data to make decisions.

Continue readingWe will be taking an example of a classification problem with the help of KNearestNeighbors in Scikit-Learn.

Continue readingIn machine learning, Classification is a supervised learning approach in which the computer program learns from the data input given to it and then classify it.

Continue reading