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  • Introduction Of Machine Learnig (Advance)

    2 Days | 18 hrs

    Mathematics for Machine Learning
    1. Introduction to Calculus, Linear Algebra, Probability, Statistics and Random Variables
    2. Introduction to Python, numpy, pandas etc.
    3. Python assignments.

    Machine Learning Basics
    1. Fundamentals of Machine Learning
    2. Application in Machine Learning- Classification, Regression etc.
    3. Introduction to the theory and algorithms of :
    → Supervised Learning
    → Semi Supervised Learning
    → Unsupervised Learning
    → Graphical Models
    → Predictive Modelling

    Practical Machine Learning-Frameworks
    1. Machine Learning Frameworks :
    → Google COLAB
    → Sci-kit-learn
    → TensorFlow
    → PyTorch
    → Keras
    2. Industry grade tools and technologies for implementing a practical machine learning project
    3. Assignments – classification, regression and mathematical models
    Quiz

    Neural Network and Deep Learning
    1. Introdution to theory of neural networks and stochastic gradient descent
    2. Deep neural networks, CNN, RNN, Auto Encoders
    3. LSTM, GAN, Capsule networks

    Practical Machine Learning – Your own models
    1. Implementing a Neural Network from scratch
    2. Implementing a Deep Neural Network (CNN, RNN, GAN) in Tensorflow/PyTorch
    3. Developing AI projects and practical caveats in implementing machine learning models
    4. Organizing Machine Learning Projects

    Research and Applications
    1. Applications of AI in Industry and Academia
    2. Computer Vision
    3. Natural Language Processing
    4. What’s hot in AI research – a discussion on state of the art and recent trends in AI
    Quiz

    Apply Course
  • Introduction Of Machine Learnig (Basic)

    Day 1 | 8 hrs

    Mathematics for Machine Learning 
    1. Introduction to Calculus
    2. Introduction to Linear Algebra
    3. Introduction to Probability & Statistics

    Machine Learning Basics
    1. Fundamentals of Machine Learning
    2. Machine Learning Practical Applications: Classification, Regression etc.
    3. Supervised Learning
    4. Semi Supervised Learning
    5.Unsupervised Learning
    6. Neural Networks and Deep Learning

    Practical Machine Learning
    1. Machine Learning Frameworks : Python, Google COLAB, TensorFlow, Pytorch, Keras
    2. Code Classification and Time series Prediction Models
    3. Implementing a Neural Network from Scratch

    Quiz

    Apply Course
  • Deep Learning For Creating Digital Content

    2 hrs

    Learn character animation, transferring styles between images and videos, denoising images using neural networks.

    PREREQUISITES: Basic familiarity with deep learning concepts, such as CNNs and experience
    with Python.
    TOOLS AND FRAMEWORKS: TensorFlow, Torch .
    LANGUAGES: English
    DURATION: 2 hours

     
    Apply Course

  • Coarse-to-Fine Contextual Memory for Medical Imaging

     2 hrs

    Learn how to improve traditional architectures using coarse-to-fine context memory. Apply it to medical image segmentation and classification tasks.

    PREREQUISITES: Experience with CNNs and long short-term memory (LSTM)
    TOOLS AND FRAMEWORKS:TensorFlow
    LANGUAGES:English
    DURATION:2 hours

     
    Apply Course

  • Deep Learning for Intelligent Video Analytics

    2 hrs

    Learn to develop deep neural networks for object detection, localization and tracking.

    PREREQUISITES: Experience with deep networks (specifically variations of CNNs) and intermediate level experience with C++ and Python.
    TOOLS AND FRAMEWORKS: TensorFlow
    LANGUAGES: English
    DURATION: 2 hours

    Apply Course
  • Applications of AI for Anomaly Detection

    2 hrs

    Learn to detect anomalies in large data sets to identify network intrusions using supervised and unsupervised machine learning techniques, such as accelerated XGBoost, autoencoders, and generative adversarial networks (GANs).
    PREREQUISITES: Experience with CNNs and Python
    TOOLS AND FRAMEWORKS: Keras, GANs
    LANGUAGES: English
    DURATION: 2 hours

    Apply Course
  • Clustering

    2 hrs

    Learn the theoretical foundations of clustering along with fundamental and advanced clustering methods such as distance based, iterative, hierarchical, continuous and categorical, density based methods. Dive into a deeper analysis with measures to analyze quality of clustering and its applications.
    PREREQUISITES: Basic machine learning and python.
    TOOLS AND FRAMEWORKS: Python, sci-kit learn, Tensor flow.
    LANGUAGES: English
    DURATION: 2 hours

    Apply Course
  • Deep Learning

    4 hrs

    PREREQUISITES:Neural Networks and python
    TOOLS AND FRAMEWORKS:Tensorflow, Keras, PyTorch
    LANGUAGES:English
    DURATION:4 hours

    Apply Course
  • Deep Learning Network Optimization

    4 hrs

    PREREQUISITES: Neural Networks and python.
    TOOLS AND FRAMEWORKS: Tensorflow, Keras, PyTorch
    LANGUAGES: English
    DURATION: 4 hours

    Apply Course
  • Silverstone Hydrogon D120 ARGB CPU Air Cooler

    Brand: Silverstone

    Model: Hydrogon D120 ARGB

    Taipei, Taiwan, January 28th, 2021 – SilverStone Technology, an established leader in the PC component field, is excited to announce the availability of the new Hydrogon D120 ARGB CPU air cooler, providing new and improved cooling solution for PC and small form factor enthusiasts.

  • LAPCARE LHOADSM1515 65 W Adapter

    400.00

    Brand: Lapcare

    Model: LAPCARE LHOADSM1515 65 W Adapter

    Overview:

    A laptop adapter is crucial for the smooth use of the device, as it enables you to charge your laptop batteries with ease. Each brand and model has a specific laptop power adapter that is compatible with it. Thus it is important to know your laptop model well before you purchase a replacement adapter for it. Proper voltage, watts and amperage of your laptop model are some essentials that you need to keep in mind. Lapcare brings you one the finest and largest range of laptop adapters. Compatible with different brands and models, these adapters come with a warranty of 12 months. Apart from this it also comes with a unique lapcare protection plan which insures your connected equipment to the adapter.

    13 Units [400/per unit]

  • LAPCARE LHOADSM1517 ADAPTER

    450.00

    Brand: Lapcare

    Model: LAPCARE LHOADSM1517 Adapter

    Overview:

    • Low Ripple operating noise
    • High gloss casing
    • Small 3-pin AC input
    • High-efficiency power Conversion ratio
    • Over current, Over voltage, Short circuit & Over temperature protection
    • Design to support low voltage input (100 v A/C)
    • Lapcare Adapter for HP 19v 4.74A 90W Smart Pin

    11 Units [450/per unit]

  • LAPCARE 65W 1525 65 W Adapter

    500.00

    Brand: Lapcare

    Model: LAPCARE 65W 1525 65 W Adapter

     

  • LAPCARE 1530 Adapter

    500.00

    Brand: Lapcare

    Model: LSOADNP1530

    Unit: 6

    Overview:

    A laptop adapter is crucial for the smooth use of the device, as it enables you to charge your laptop batteries with ease. Each brand and model has a specific laptop power adapter that is compatible with it. Thus it is important to know your laptop model well before you purchase a replacement adapter for it. Proper voltage, watts and amperage of your laptop model are some essentials that you need to keep in mind.

    Lapcare brings you one the finest and largest range of laptop adapters. Compatible with different brands and models, these adapters come with a warranty of 12 months. Apart from this it also comes with a unique lapcare protection plan which insures your connected equipment to the adapter.

    Features:

    High-efficiency power conversion ratio and low ripple operating noise lpp

    High-gloss casing

    Over current protection / Over voltage protection / Short circuit protection / Over temperature protection

  • Godrej ST-PS04P04

    541.00

    Brand : Godrej

    Model No. : ST-PS04P04

    Channel : 4

    Current : 4

    Over current Protection : Yes

    Over Voltage Protection : Yes

    Short Circuit Protection : Yes

    Body : Plastic

    Long Distance Clamp Regulator : Yes