Machine Learning is a multi-disciplinary field that covers many subjects such as mathematics and programming languages. With the help of Machine learning, we can draw the meaningful inferences from previous experiences. Machine Learning can be used any various fields such as finance, data analysis, robotics, Marketing, Healthcare and sales, Transportation etc,.

Many companies such as Facebook, Google, Amazon, Microsoft, Intel, Wix, Quora, etc,. have already indulged the machine learning algorithms to improve the quality of services. Facebook uses Face detection, Friend suggestions algorithms etc,. Google uses machine learning algorithms for video recommendations(YouTube), online advertising(AdSense, Real-time Bidding), Search engines. Quora uses machine learning for showing personalized feed based on their user's interest.

Read: Top 10 applications of Machine Learning

The demand for the Machine learning has increased over the past few years and companies are looking for the employees who have skills in Machine Learning and Data Science. There are many resources to learn Machine learning but the below resources helps to master Machine Learning.

Read: Top 10 Data Science video tutorials

To learn machine learning, you need to have prior knowledge of mathematical concepts such as Calculus, Linear, Algebra, Probability, Statistics, And also you need knowledge of any programming language Python, R, or Matlab.

Read: Top 10 Best Python video tutorials

Read: Top 10 Best R Programming video tutorials

It is also worth to watch these tutorials as well Intel Nervana AI Academy and Machine_Learning

Happy Learning :)

Many companies such as Facebook, Google, Amazon, Microsoft, Intel, Wix, Quora, etc,. have already indulged the machine learning algorithms to improve the quality of services. Facebook uses Face detection, Friend suggestions algorithms etc,. Google uses machine learning algorithms for video recommendations(YouTube), online advertising(AdSense, Real-time Bidding), Search engines. Quora uses machine learning for showing personalized feed based on their user's interest.

Read: Top 10 applications of Machine Learning

The demand for the Machine learning has increased over the past few years and companies are looking for the employees who have skills in Machine Learning and Data Science. There are many resources to learn Machine learning but the below resources helps to master Machine Learning.

Read: Top 10 Data Science video tutorials

To learn machine learning, you need to have prior knowledge of mathematical concepts such as Calculus, Linear, Algebra, Probability, Statistics, And also you need knowledge of any programming language Python, R, or Matlab.

Read: Top 10 Best Python video tutorials

Read: Top 10 Best R Programming video tutorials

### Machine Learning

This is a popular video tutorial over the internet which gives the best introduction to machine learning octave/Matlab handling by Andrew Ng who is the co-founder of Coursera. This tutorial is well presented and the instructor provides lots of practical suggestions on how to analyze and improve existing machine learning algorithms. The instructor walks you through the supervised learning such as parametric/non-parametric algorithms, support vector machines, kernels, neural networks and unsupervised learning such as clustering, dimensionality reduction, recommender systems, deep learning. The best thing about this course, you will learn how to apply the knowledge acquired in real-time such as perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas. This course provides hands-on assignments, quizzes, which allows you to a good understanding of these contents and to boost your confidence. I bet you won't be regretting after going through this course and you won't leave without the appreciating the instructor. I highly recommend this course for those who want to get started with machine learning for both technical and non-technical background as well.

This is another popular video tutorial over the web and it gives a comprehensive overview of the machine learning. This is very good tutorial to get started with machine learning which provides step by step insight into Machine Learning. This course is divided into 10 sections and the instructor begins with explaining applications of the Machine learning and shows how to setup the environment for Python and R language. In the first the section, you will learn about data processing and how to obtain the meaningful inferences from the data. In the second section, you will learn about regression analysis, how to use regression analysis and what are different types of regression analysis such as Linear Regression, Logistic Regression, Polynomial Regression, Stepwise Regression, Ridge Regression, Lasso Regression, ElasticNet Regression etc,. In 3rd sections, you will learn about classification and different methods of classification such as Logistic Regression, K-Nearest Neighbours, Support Vector Machines, Kernel Support Vector Machines, Naive Bayes, Decision Tree Classification, Random Forest Classification. In the 4th section, the instructor walks you through Clustering and its methods K-Means, Hierarchical Clustering. Each section covers such as Association Rule Learning, Reinforcement Learning, Natural Language Processing, Deep Learning, Dimensionality Reduction, Model Selection & Boosting. All these concepts help to master in machine learning. This course is best suitable for aspirants who want to build a career in Data Science and enhance their skills in Machine Learning.

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### Data Science, Deep Learning, & Machine Learning with Python

This tutorial gives you a comprehensive overview of the machine learning, data Science, and deep learning. In the tutorial, the instructor gives a basic introduction of Python programming, Statistics, and probability and then covers topics of data mining, Artificial intelligence, machine learning such as Bayesian theorem, regression analysis, K-means Clustering, principle component analysis, decision and much more,. The instructor also shows how to create the Artificial Neural Networks with Tensorflow and Keras. Here, you will not only the learn theory but you will also learn how to create the recommender system, spam classifier, search engine, Handwriting recognization, sentimental analysis practically. The instructor keeps motivating and explains the concepts without any complexity. This video tutorial is best suitable for the beginners.### Machine Learning Recipes with Josh Gordon

This tutorial is presented by Google Developers and Josh, the instructor of this tutorial walks you through concepts of the Machine learning with the help of the popular libraries called Tenserflow and Scikit-Learn. He explains how to install Anaconda and use of classifiers under supervised learning. He also explains the decision trees, k-Nearest Neighbors etc,. I would recommend this without a miss. This video tutorial is completely for the beginners and who already have knowledge of Python programming.### Python for Data Science and Machine Learning Bootcamp

This video tutorial is designed for both beginners and data scientists. I would say this video tutorial will be helpful to the job seekers and data scientists who want to build their career in machine learning. In this video tutorial, you will learn the use of Python for machine learning and Data science. You will able to learn how to implement the machine learning algorithms.### Machine Learning with Python

This tutorial is presented by Sentex that is popular Youtube channel for learning Python-based programming. Here you can also find tutorials on Python programming for web development, Machine learning, finance, data analysis, robotics, web development, game development and more. In this video tutorial, the instructor walks you through the Machine learning concepts such as Regression, classification, support vector machines, clustering, deep learning and tenser flow neural networks, convolutional neural network etc,. This tutorial is best suitable for the beginners and intermediate.### [Coursera] Neural Networks for Machine Learning — Geoffrey Hinton 2016

This tutorial mainly focuses on explaining how Neural Networks are used for Machine learning in speech, object recognization and image segmentation, modeling language, human motion etc,. Geoffrey walks you through the machine learning algorithms and how these algorithms help us in achieving the speech, object recognization and image segmentation, human motion.### Machine learning in Python with scikit-learn

This tutorial primarily focuses on explaining how to use Scikit-learn library for Machine Learning. Here the instructor begins with a quick introduction of machine learning and how it is used, then he walks you through how to set up an environment for working with Scikit-learn library, the instructor shows how to install Anaconda and configures the IPython interpreter. He also concepts such as training the models, comparing the models, pandas, Seaborn, selecting the best models, how to evaluate the classifier etc,. It is worth to go through this tutorial. This tutorial is best suitable for the intermediates.###

Machine Learning: IIT Lectures/Tutorial/Course for Beginners

This tutorial is presented by IIT university and they have published around 85 videos that help to understand basic concepts of machine learning. The instructor also explains the different machine learning paradigms and they also cover some of the most popular machine learning paradigms and architecture. In this tutorial, you will learn about the Linear Regression and Feature Selection, Linear Classification, Support Vector Machines and Artificial Neural Networks, Bayesian Learning and Decision Trees, Evaluation Measures, Hypothesis Testing, Ensemble Methods, Clustering, Graphical Models, Learning Theory and Expectation Maximization, Introduction to Reinforcement Learning etc,. I would recommend taking advantage of this tutorial.

### Machine Learning Course - CS 156

This video tutorial is a best introductory course on machine learning by Yaser Abu-Mostafa and the instructor walks you basic theory, machine learning algorithms and it's applications. This video tutorial balances both theory and practice and also covers the mathematical as well as the heuristic aspects. I recommend going through with 1.25x to speed up your learning. If you are complete beginner then I would suggest going through this tutorial without a miss.

It is also worth to watch these tutorials as well Intel Nervana AI Academy and Machine_Learning

From every video tutorial, you will learn something new, so I believe that

**the more you explore, the more you learn**Happy Learning :)