Knowledge in Machine learning
electrical machine - 2
The induction machine was invented by NIKOLA TESLA in 1888. Right from its inception its ease of manufacture and its robustness have made it a very strong candidate for electromechanical energy conversion. It is available from fractional horsepower ratings to megawatt levels. It finds very wide usage in all various application areas. The induction machine is an AC electromechanical energy conversion device. The machine interfaces with the external world through two connections (ports) one mechanical and one electrical. The mechanical port is in the form of a rotating shaft and the electrical port is in the form of terminals where AC supply is connected. There are machines available to operate from three phase or single phase electrical input. In this module we will be discussing the three phase induction machine. Single phase machines are restricted to small power levels.
Shantha Kumar . V
electrical machine -1 - part 2
Electromechanical Energy conversion, forces and torque in magnetic field systems – energy balance, energy and force in a singly excited magnetic field system, determination of magnetic force , coenergy, multi excited magnetic field systems. DC Generators – Principle of operation, Action of commutator, constructional features, armature windings, lap and wave windings, simplex and multiplex windings, use of laminated armature, E. M.F. Equation, Methods of Excitation: separately excited and self excited generators, build up of E.M.F., critical field resistance and critical speed , causes for failure to self excite and remedial measures, Armature reaction: Cross magnetizing and demagnetizing AT/pole, compensating winding, commutation, reactance voltage, methods of improving commutation Load characteristics of shunt, series and compound generators, parallel operation of DC generators, use of equalizer bar and cross connection of field windings, load sharing. MODULE-II (10 HOURS) Transformers: Single phase transformer, Constructional details, Core, windings, Insulation, principle of operation, emf equation, magnetising current and core losses, no load and on load operation, Phasor diagram, equivalent circuit, losses and efficiency, condition for maximum efficiency, voltage regulation, approximate expression for voltage regulation, open circuit and short circuit tests, Sumpner’s test, Inrush of switching currents, harmonics in single phase transformers, magnetizing current wave form, Parallel operation of transformers. MODULE-III (10 HOURS) DC Motors: Principle of operation, Back E.M.F., Torque equation, characteristics and application of shunt, series and compound motors, Armature reaction and commutation, Starting of DC motor, Principle of operation of 3 point and 4 point starters, drum controller, Constant & Variable losses, calculation of efficiency, condition for maximum efficiency.
Classification errors, regularization, logistic regression
Classification errors, regularization, logistic regression
Tanmay Mondal
Linear regression, estimator bias and variance, active learning
Linear regression, estimator bias and variance, active learning
Active learning (cont.), non-linear predictions, kernals
Active learning (cont.), non-linear predictions, kernals
Kernal regression and kernels
Kernal regression and kernels of machine learning
Support vector machine (SVM) and kernels, kernel optimization
Support vector machine (SVM) and kernels, kernel optimization
Model selection
Model selection in machine learning
Model selection criteria
Model selection criteria in machine learning
Description length, feature selection
Description length, feature selection of model
Machine learning with Python
Syllabus for Machine Learning with Python Programming Language
Ankush Saha
Machine learning syllabus
Syllabus of Machine Learning
Chandan Dey