About Machine Learning

Aedifico is the pioneer in providing technical training to the professionals and to the students. Machine learning is the domain where algorithms and statistics come together and make the innovative concepts like prediction, recognition and forecasting. Various processes involved in preparing raw data of any vertical (finance, Electrical, Electronics, Healthcare etc.) into the data ready to be processed in the algorithms related to machine learning. Right from the pre-processing stage followed by training stage and then the testing stage. All the stages are comprehensively covered in the machine learning training program.

Aedifico provides a best in class training on machine learning in Delhi with real problem statement solving assignments to impart a practical hands-on knowledge to the aspiring candidates. Various case studies will be shared during the training tenure for an enrich projects experience.

Course Highlights

  • Mathematical Computing with Python
    Introduction to Numpy
    Class and Attributes of ndarray
    Mathematical Functions of Numpy
    Scientific computing with Python
    Scipy module
    Integration and Optimization
    Eigenvalues and Eigenvector
    Sub Package-Statistics, Weave and IO
    Data Manipulation
    Understanding DataFrame
    Using Pandas module
    Importing data from various sources (csv, txt, excel)
    Sorting, filtering, duplicates, merging, appending,
    subsetting, sampling, formatting
    stripping out extraneous information
    Normalizing data
    Introduction to Machine Learning
    What is Machine Learning?
    When should we use Machine Learning?
    Prediction and Forecasting Analysis
    Machine Learning Approaches and Predictive Modelling
    Supervised Learning vs Unsupervised Learning
    Regression vs Classification vs Segmentation vs forecasting
    Supervised Learning
    What is supervised learning?
    Support Vector Machine Introduction
    Preparing Data for SVM training
    Kernel function selection for specific data
    Testing of DATA using SVM classify function
    How binary SVM is modified for Multi class as multi class SVM
    Face recognition case study using SVM on ORL dataset
    Neural network implementation
    Training Neural Network using LM training function
    Viewing the Network
    Validating the network
    Testing the Network
    Comparison of results of SVM and Neural network
    Unsupervised Learning
    What is unsupervised learning?
    Clustering Algorithms Groups the data together based on the data features
    K-means Clustering
    Fuzzy C-means Clustering
    Self Organising Maps
    Gaussian Mixture Model
    Introduction to Deep Learning
    Convolutional Neural Network
    Digit Recognition system implementation using CNN
    Deep Belief Neural Network
    Digit Recognition system implementation using DNN
    Dimensionality Reduction Technique
    PCA – Principal Component Analysis
    Non Negative Matrix Factorization
    Case Studies
    Color Based Segmentation using Fuzzy C means
    Color Based image segmentation using K-means
    Face Recognition system using support Vector Machine
    Face recognition using Neural Networks
    Real time Gesture Recognition system implementation using CNN deep learning method

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