Adapter Connectors

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Adapter Connectors Results:
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RJJU-66-143-E1V-014
Encitech Connectors
Quantity: 3000
Ship Date: 9 weeks
150+ $1.0024
- +
x $1.0024
Ext. Price: $300.72
MOQ: 300
Mult: 150
SPQ: 150
RJJU-88-143-E7V-012
Encitech Connectors
Quantity: 1800
Ship Date: 9 weeks
90+ $0.8643
- +
x $0.8643
Ext. Price: $311.14
MOQ: 360
Mult: 90
SPQ: 90
CP30220SMB
CLIFF Electronic
adapter, FTP, RJ45, mother, 8P8C, CAT5E;
Quantity: 49
Ship Date: 3-12 working days
1+ $8.4009
10+ $7.8409
25+ $7.7008
50+ $7.5608
250+ $7.5608
- +
x $8.4009
Ext. Price: $16.80
MOQ: 2
Mult: 1
CP30220M
CLIFF Electronic
UTP ADAPTER, RJ45, JACK, 8P8C, CAT5E;
Quantity: 77
Ship Date: 3-12 working days
1+ $7.0335
10+ $6.302
25+ $6.302
50+ $6.077
250+ $6.077
- +
x $7.0335
Ext. Price: $14.06
MOQ: 2
Mult: 1
RJJU-88-142-E1V-021
Encitech Connectors
Quantity: 3200
Ship Date: 9 weeks
160+ $1.0365
- +
x $1.0365
Ext. Price: $331.68
MOQ: 320
Mult: 160
SPQ: 160
RJJU-88-142-E7V-023
Encitech Connectors
Quantity: 1400
Ship Date: 9 weeks
70+ $1.6587
- +
x $1.6587
Ext. Price: $348.32
MOQ: 210
Mult: 70
SPQ: 70
CP30220S
CLIFF Electronic
adapter, FTP, RJ45, mother, 8P8C, CAT5E;
Quantity: 293
Ship Date: 3-12 working days
1+ $7.4091
10+ $6.6386
25+ $6.6386
50+ $6.4015
250+ $6.4015
- +
x $7.4091
Ext. Price: $14.81
MOQ: 2
Mult: 1
RJJS-88-142-E7H-020
Encitech Connectors
Quantity: 1600
Ship Date: 9 weeks
80+ $1.981
- +
x $1.981
Ext. Price: $316.95
MOQ: 160
Mult: 80
SPQ: 80
211B-11C0A-R
Attend Technolog
Modular Jack RJ45 8P8C THT horiz.LED Y/G
Quantity: 1100
Ship Date: 12-16 working days
1+ $0.6844
- +
x $0.6844
Ext. Price: $496.19
MOQ: 725
Mult: 1
SPQ: 1
CP30220SX
CLIFF Electronic
adapter, FTP, RJ45, mother, 8P8C, CAT5E;
Quantity: 246
Ship Date: 3-12 working days
1+ $8.529
10+ $7.642
25+ $7.5056
50+ $7.369
250+ $7.369
- +
x $8.529
Ext. Price: $17.05
MOQ: 2
Mult: 1
RJJS-88-142-E7V-022
Encitech Connectors
Quantity: 65
Ship Date: 12-14 working days
5+ $1.981
- +
x $1.981
Ext. Price: $295.16
MOQ: 149
Mult: 1
SPQ: 80
RJJU-88-141-E3H-009
Encitech Connectors
Quantity: 180
Ship Date: 12-14 working days
120+ $1.0365
- +
x $1.0365
Ext. Price: $373.14
MOQ: 360
Mult: 120
SPQ: 120
MP0050
LogiLink
Quantity: 5
Ship Date: 7-15 working days
1+ $3.8554
- +
x $3.8554
Ext. Price: $92.52
MOQ: 24
Mult: 1
SPQ: 1
1794
Pomona Electronics
BNC FEMALE TO WE-309 PHONE PLUG
Quantity: 0
Ship Date: 7-12 working days
2+ $53.9892
- +
x $53.9892
Ext. Price: $107.97
MOQ: 2
Mult: 2
SPQ: 1
7020
Keystone Electronics
Conn BNC-Banana Plug Adapter M/PL 1/2 POS ST
Quantity: 0
Ship Date: 6-13 working days
500+ $13.041
- +
x $13.041
Ext. Price: $6520.50
MOQ: 500
Mult: 1
SPQ: 1
1285
Pomona Electronics
PHONE PLUG ADAPTER WITH BINDING POSTS Brass Nickel
Quantity: 0
Ship Date: 7-12 working days
- +
x $
Ext. Price:
MOQ: 1
Mult: 1
SPQ: 1

Adapter Connectors

Adapter Transfer, also known as transfer learning, is a machine learning technique where a model developed for a specific task is reused as the starting point for a model on a second task. This approach is particularly useful when the second task has limited data available for training.

Definition:
Transfer learning is a subset of machine learning that involves taking a pre-trained model from one domain and applying it to a different but related domain. The idea is to leverage the knowledge gained from the first domain to improve the performance on the second domain, often with less data and computational resources.

Function:
The primary function of transfer learning is to enhance the performance of a model by transferring the knowledge from a source task to a target task. This is achieved by fine-tuning a pre-trained model on a new dataset, which allows the model to adapt to the specific characteristics of the new task without starting from scratch.

Applications:
1. Natural Language Processing (NLP): Pre-trained models like BERT or GPT can be fine-tuned for tasks such as sentiment analysis, text classification, or machine translation.
2. Computer Vision: Models trained on large datasets like ImageNet can be adapted for object detection, image segmentation, or facial recognition in different contexts.
3. Speech Recognition: Pre-trained models can be fine-tuned for specific accents or languages, improving recognition accuracy.
4. Medical Imaging: Models trained on general image data can be adapted to detect specific medical conditions by transferring the learned features to the medical domain.

Selection Criteria:
When choosing an adapter transfer model, consider the following criteria:
1. Relevance: The source task should be closely related to the target task to ensure effective knowledge transfer.
2. Performance: The pre-trained model should have demonstrated strong performance on its original task.
3. Data Availability: The target task should have limited labeled data, as transfer learning is particularly beneficial in such scenarios.
4. Computational Resources: Transfer learning can be more computationally efficient than training a model from scratch, especially when resources are limited.
5. Domain Specificity: The model should be adaptable to the nuances of the target domain, which may require domain-specific fine-tuning.

In summary, adapter transfer is a powerful technique in machine learning that allows for the efficient use of pre-trained models to tackle new tasks with limited data. It is selected based on the relevance of the source task, the performance of the pre-trained model, and the specific needs of the target domain.
Please refer to the product rule book for details.