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This document provides an overview of getting started with machine learning and deep learning. It outlines learning roadmaps that involve studying Python/R, machine learning, and Kaggle competitions. It also lists relevant online courses from Coursera and recommends resources like the Taiwan AI Academy. The document advises obtaining an Nvidia GPU like the GTX 1060, 1070 or 1080 to accelerate deep learning and suggests a gaming PC or notebook for the GPU. It concludes by providing contact information.
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Example: For NP-Hard Problems, approximation algorithms are used. Sorting algorithms are the exact algorithms.
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Practice Head Torpedo - Neometrix Defence.pptx
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About
Practice Head is assembled with Practice Torpedo intended for carrying out exercise firings. It is assembled with Homing Head in the forward section and oxygen flask in the rear section. Practice Head imparts positive buoyancy to the Torpedo at the end of run. The Practice Head is divided into two compartments viz. Ballast Compartment (Houses Light Device, Depth & Roll Recorder, Signal Flare Ejector, Discharge Valve, Stop Cock, Water discharge Valve, Bellow reducing Valve, Release Mechanism, Recess, Bypass Valve, Pressure Equalizer, Float, Sinking Plug etc.) which provides positive buoyancy at the end of run by discharging water (140 ltrs.) filled in the compartment and Instrument compartment (dry), houses (safety & recovery unit and its battery, combined homing and influence exploder equipment, noise maker, bollards & safety valve etc.) The recess in Ballast compartment houses the float which gets inflated at the end of run to provide floatation to the surfaced Torpedo. Several hand holes/recesses are provided on the casing/shell of Practice Head for assembly of the following components:-
a) Signal Flare Ejector Assembly
b) Depth and Roll Recorder Assembly
c) Light Device
d) Pressure equalizer
e) Drain/Discharge Valve assembly
f) Bollard Assembly
g) Holding for Floater/Balloon Assembly
h) Sinking Valve
i) Safety Valve
j) Inspection hand hole
Technical Details:
SrNo Items Specifications
1 Aluminum Alloy (AlMg5)
Casing Body Material: AlMg5
? Larger Outer Diameter of the Casing: 532.4 MM
? Smaller Outer Diameter of the Casing: 503.05 MM
? Total Length: 1204.20 MM
? Thickness: 6-8 mm
? Structural Details of Casing: The casing is of uniform outer dia for a certain distance from rear side and tapered from a definite distance to the front side. (Refer T-DAP-A1828-GADWG-PH- REV 00)
? Slope of the Tapered Portion: 1/8
? Mass of Casing (Without components mounting, but including the ribs and collars on the body): 58.5 kg
? Maximum External Test Pressure: 12 kgf/cm2
? Maximum Internal Test Pressure:-
i. For Ballast Compartment: 2 kgf/cm2
ii. For Instrument Compartment: 1 kgf/cm2
? Innerspace of casing assembly have 2 compartments:-
i. Ballast Compartment and
ii. Instrument Compartment
? Cut outs/ recesses shall be provided for the assembly of following components.
a) Signal Flare Ejector Assembly
b) Depth and Roll Recorder Assembly
c) Light Device
d) Pressure Equalizer
e) Drain/ discharge valve assembly
2 Front Side Collar Material: AlMg5
? Maximum Outer Diameter: 500 MM
? Pitch Circle Diameter: 468 MM
? All Dimensions as per drawing T-DAP-A1828-MDWG-C&R-REV-00
Application:
In a torpedo, the ballast components and instrument compartment play crucial roles in maintaining stability, control, and overall operational effectiveness. The ballast system primarily manages buoyancy and trim, ensuring that the torpedo maintains a stable trajectory underwater.Common Network Architecture:X.25 Networks, Ethernet (Standard and Fast): fram...
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- 1. Getting Start Deep Learning or Machine Learning with Kaggle a, Andrew Wang lƼ g 2018/01/27
- 2. Artificial Intelligence Machine Learning Deep Learning IBM Deep Blue Google Search AlphaGo
- 3. Learning Roadmap for Machine Learning Study Python/R Study Machine Learning Kaggle
- 4. Coursera for Machine Learning https://www.coursera.org/learn/machine-learning
- 5. Learning Roadmap for Deep Learning Study Python Study Machine Learning Kaggle Study Deep Learning
- 6. Coursera for Deep Learning https://www.coursera.org/specializations/deep-learning
- 7. Other Resources ? ̨˹ǻیWУ http://aiacademy.tw/ ? Stanford: Convolutional Neural Networks for Visual Recognition http://cs231n.stanford.edu/ ? ̨ώ CWn http://speech.ee.ntu.edu.tw/~tlkagk/co urses.html
- 8. GPU in Deep Learning for Getting Start ? nVidia GPU C GTX 1060 C GTX 1070 C GTX 1080 C GTX 1080 Ti (Time is money!)
- 9. Gaming PC or NB for GPU ? XXX