Machine Learning Tutorial Series and learn ML from Scratch

Machine learning tutorials for beginners - Know what is machine learning and learn its concepts from basic to advanced in simple and easy way

Top 9 Machine Learning Applications For Real time - What are Applications of Machine Learning,Image Recognition,Speech Recognition,Learning Associations

Learn about the three different types of machine learning algorithms - supervised, unsupervised & reinforcement learning with use cases of Baidu,Google AQA

Top machine learning tools that are helping big brands to improve their performance. Scikit-learn, NLTK, PyTorch, SAS, Numpy & many other that you must read

Future of Machine learning -What is Machine Learning,Machine learning algorithms,applications of Machine learning,machine learning trends,companies using ML

Machine Learning Algorithms-Types of ML Algorithms: Supervised, Unsupervised, Semi-Supervised, Regression, Instance-based,Regularization, Decision Tree

Learn the Advantages and Disadvantages of Machine Learning Language to know where to use or where not to use ML and also its benefits and limitations

Transfer Learning-what is transfer learning in deep learning,ways to fine tune the models, pre-trained model and its use,how &when to use transfer learning,

10 best libraries for machine learning in Java - DL4J - deep learning, ADAMS, JavaML, Mahout, Neuroph, RapidMiner, Weka, JSTAT, ELKI, Stanford CoreNLP

Learn everything about neural networks in artificial intelligence. Know what is artificial neural network, how it works. ANN with example and types.

Artificial Neural Network Applications - What are Applications of ANN, Handwriting recognition,Travelling salesman,Medical Diagnosis,face & Fraud Detection

Top 5 Learning Rules in Neural Network-Hebbian Learning,Perceptron learning algorithum,Delta learning rule,Correlation Learning in Artificial Neural Network

Artificial neural network model covers Multilayer perceptron network,Radial Basis function,Kohonen network,Multilayer perceptron vs Radial Basis Function

Artificial Neural Network Algorithms to Train ANN- Gradient Descent algorithm,Genetic Algorithm & steps to execute genetic algorithms,Evolutionary Algorithm

Deep Learning Tutorial - Learn what is deep learning and neural networks in Machine learning and various use cases and applications of deep learning

Deep Learning Terminologies-Deep Learning Terms,RNN,Neural networks,learning rate,gradient decsent,activation function,backpropogation,data augmentation

Audio Analysis Using Deep Learning, Introduction to Audio Analysis, Data Handling in Audio Domain, Applications of Audio Processing and audio data analysis

Applications of SVM-face detection,image classification,bioinformatics,Text categorization, Generalized Predictive Control(GPC),Geo & Environmental Sciences

Introduction to SVM Kernel & Kernel Functions-Polynomial,Gaussian,RBF,Laplace RBF,Hyperbolic tangent kernel,Bessel function,ANOVA radial basis,Linear spline

What is Dimensionality reduction- dimension reduction technique, Methods & importance of dimension reduction, Advantages & Disadvantages of Dimensionality

What is Gradient Boosting Algorithm- Improvements & working on Gradient Boosting Algorithm, Tree Constraints, Shrinkage, Random sampling, Penalized Learning

XGBoost Tutorial - What is XGBoost,Why we use XGBoost Algorithms:, Why XGBoosting is good, Learn features of XGBoost: Model, System, Alorithms Features

What is XGBoost Algorithm-Preparation of Data with XGBoost,Building Model using Xgboosting on R,Parameters used in Xgboost,Advanced functionality of xgboost

What is AdaBoost, AdaBoost Algorithm Model, Ada Boosting Ensemble, Making Predictions & Data Preparation for AdaBoost, AdaBoost Example, adaptive boosting

Deep Learning vs Machine Learning - A feature-wise comparison. Learn What is deep learning and machine learning with their future and applications