Our Machine Learning Course Training Details

SocialPrachar is Pioneer in Corporate Trainings for Machine learning Course Training in Hyderabad with real-time experts and certification. We are one of the few companies in hyderabad which are offering Advanced Machine learning course with data science includes Python,Deep Learning,R,SQL etc. Successfully Trained Around 100’s of Trainees on Machine Learning in our training Center located at KPHB,Hyderabad.  

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    Classroom Training at our Hyderabad Training Center
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    See all our Upcoming Machine Learning with Data Science training schedules here

    PARTICULARS

    MACHINE LEARNING

    [Regular]

    ₹ 22,000

    MACHINE LEARNING

    [Advanced]

    ₹ 30,000

    MACHINE LEARNING

    [Advanced + Internship]

    ₹ 55,000

    Python

    Machine Learning Supervised

    Machine Learning UnSupervised

    Hadoop | SQL

    Text Processing on Data

    Deep Learning with Tensorflow

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    Neural Networks

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    NLP

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    Computer Vision

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    Client Internship

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    Capstone Projects 5 8 10
    Duration
    3 months
    4 months
    6 months
    Learning Hours
    110 hours
    160 hours
    300 hours
    Projects
    30 hours
    70 hours
    150 hours
    Timings
    Morning & Evening
    Morning & Evening
    Morning & Evening
    DIY Assignments
    20
    30
    50
    Assignment Tests
    5
    8
    10
    Learn First – Pay Next

    x

    x

    ML CAREER+ Services (Hyderabad)

    PARTICULARS

    MACHINE LEARNING

    [Regular]

    ₹ 22,000

    MACHINE LEARNING

    [Advanced]

    ₹ 30,000

    MACHINE LEARNING

    [Advanced + Internship]

    ₹ 55,000

    100% Placement Assistance (Upto 6 months)

    Resume Preparation

    Mock Interviews

    Project Submissions & Presentation

    Social Recruiting

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    Digital Learning Portal

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    Master Machine Learning Python with Certification

    Machine learning is starting to redefine the way we live, here we detailed why it matters most right now. Machine learning is nothing but an application of Artificial Intelligence (AI). It provides systems the ability to automatically learn and improve from expertise without being expressly programmed. Machine Learning gives computers the ability to “learn” (i.e., progressively improve performance on a specific task) with data, without being explicitly programmed.

    You encounter machine learning almost every day, think about

    • Ridesharing apps like Lyft & Uber – How do they determine the price of your ride?
    • Google Maps – How do they analyze traffic movement and predict your arrival time within seconds?
    • Filter spam – Emails going automatically to your spam folder?
    • Amazon Alexa, Apple SIRI, Microsoft Cortana & Google Home – How do they recognize your speech?

    Machine Learning can be categorized into three parts :

    • Supervised Learning
    • Unsupervised Learning
    • Reinforcement Learning
    1. Supervised Learning:

    Supervised Learning algorithm consists of a target/outcome variable (or dependent variable) which is to be predicted from a given set of predictors (independent variables). Using these set of variables, we generate a function that map inputs to desired outputs. The training process continues until the model achieves a desired level of accuracy on the training data.

    1. Unsupervised Learning:

    In Unsupervised Learning algorithm, we do not have any target or outcome variable to predict / estimate. It is used for clustering population in different groups, which is widely used for segmenting customers in different groups for specific intervention.

    3. Reinforcement Learning:

    Using this Reinforcement Learning algorithm, the machine is trained to make specific decisions. It works this way: the machine is exposed to an environment where it trains itself continually using trial and error. This machine learns from past experience and tries to capture the best possible knowledge to make accurate business decisions.

    Can Machine Learning Teach Us anything?

    Languages suited for Machine Learning

    • Python (best for both beginner and advanced level)
    • R (good but slow run time)
    • Matlab (good but costly and slow)
    • Julia (Future best! very fast, good, limited libraries as it is new)
    • C++ (difficult, very fast, used in production)

    Here is the list of commonly used machine learning algorithms. These algorithms can be applied to almost any data problem:

    1. Linear Regression
    2. Logistic Regression
    3. Decision Tree
    4. SVM
    5. Naive Bayes
    6. kNN
    7. K-Means
    8. Random Forest
    9. Dimensionality Reduction Algorithms
    10. Gradient Boosting algorithms
    • GBM
    • XGBoost
    • LightGBM
    • CatBoost

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