ʻO kekahi o nā mea paahana kaulana loa no ka hoʻomohala ʻana i nā hiʻohiʻona aʻo mīkini ʻo TensorFlow. Hoʻohana mākou iā TensorFlow i nā noi he nui i nā ʻoihana like ʻole.
Ma kēia pou, e nānā mākou i kekahi o nā hiʻohiʻona TensorFlow AI. No laila, hiki iā mākou ke hana i nā ʻōnaehana naʻauao.
E hele pū mākou i nā frameworks i hāʻawi ʻia e TensorFlow no ka hana ʻana i nā hiʻohiʻona AI. No laila e hoʻomaka kākou!
ʻO kahi hoʻolauna pōkole i TensorFlow
ʻO Google's TensorFlow kahi kumu wehe aʻo aʻo pūʻolo polokalamu. Loaʻa iā ia nā mea hana no ka hoʻomaʻamaʻa a me ka hoʻolaha ʻana nā mīkini aʻo mīkini ma nā paepae he nui. a me nā mea hana, a me ke kākoʻo no ke aʻo hohonu a nā hanana laulā.
Hiki iā TensorFlow nā mea hoʻomohala e hana i nā hiʻohiʻona no nā noi like ʻole. Loaʻa kēia i ka ʻike kiʻi a me ka leo, ka hana ʻōlelo kūlohelohe, a me ʻikeʻikepili. He mea hana ikaika a hiki ke hoʻololi me ke kākoʻo kaiaulu ākea.
No ka hoʻouka ʻana iā TensorFlow ma kāu kamepiula hiki iā ʻoe ke kākau i kēia ma kāu puka kauoha:
pip install tensorflow
Pehea e hana ai nā mea hoʻohālike AI?
ʻO nā hiʻohiʻona AI nā ʻōnaehana kamepiula. No laila, pono lākou e hana i nā hana e pono ai ka naʻauao kanaka. ʻO ka ʻike kiʻi a me ka ʻōlelo a me ka hoʻoholo ʻana he mau laʻana o ia mau hana. Hoʻokumu ʻia nā hiʻohiʻona AI ma nā ʻikepili nui.
Hoʻohana lākou i nā ʻenehana aʻo mīkini e hana i nā wānana a hana i nā hana. He nui kā lākou hoʻohana, me nā kaʻa kaʻa kaʻa ponoʻī, nā mea kōkua pilikino, a me nā diagnostics olakino.
No laila, he aha nā hiʻohiʻona kaulana ʻo TensorFlow AI?
ResNet
ʻO ResNet, a i ʻole Residual Network, kahi ʻano convolutional kaʻenehana kikowaena. Hoʻohana mākou no ka hoʻokaʻawale kiʻi a ʻike mea. Ua hoʻomohala ʻia e nā mea noiʻi Microsoft ma 2015. Eia kekahi, ʻike nui ʻia e ka hoʻohana ʻana i nā koena pili.
Hiki i kēia mau hoʻohui ke aʻo maikaʻi i ka pūnaewele. No laila, hiki ke hoʻoheheʻe ʻia ka ʻike ma waena o nā papa.
Hiki ke hoʻokō ʻia ʻo ResNet ma TensorFlow ma ka hoʻohana ʻana i ka Keras API. Hāʻawi ia i kahi kiʻekiʻe kiʻekiʻe, mea hoʻohana-friendly interface no ka hana ʻana a me ke aʻo ʻana i nā ʻupena neural.
Ke hoʻokomo nei iā ResNet
Ma hope o ka hoʻokomo ʻana iā TensorFlow, hiki iā ʻoe ke hoʻohana i ka Keras API e hana i kahi hoʻohālike ResNet. Loaʻa iā TensorFlow ka Keras API, no laila ʻaʻole pono ʻoe e hoʻokomo iā ia i kēlā me kēia.
Hiki iā ʻoe ke hoʻokomo i ke kumu hoʻohālike ResNet mai tensorflow.keras.applications. A, hiki iā ʻoe ke koho i ka mana ResNet e hoʻohana ai, no ka laʻana:
from tensorflow.keras.applications import ResNet50
Hiki iā ʻoe ke hoʻohana i kēia code no ka hoʻouka ʻana i nā paona i hoʻomaʻamaʻa mua ʻia no ResNet:
model = ResNet50(weights='imagenet')
Ma ke koho ʻana i ka waiwai include_top=False, hiki iā ʻoe ke hoʻohana i ke kumu hoʻohālike no ka hoʻomaʻamaʻa hou ʻana a i ʻole ka hoʻoponopono ʻana i kāu ʻikepili maʻamau.
model = ResNet50(weights='imagenet', include_top=False, input_shape=(224, 224, 3))
Nā ʻāpana hoʻohana o ResNet
Hiki ke hoʻohana ʻia ʻo ResNet i ka hoʻokaʻawale kiʻi. No laila, hiki iā ʻoe ke hoʻokaʻawale i nā kiʻi i nā hui he nui. ʻO ka mea mua, pono ʻoe e hoʻomaʻamaʻa i kahi hoʻohālike ResNet ma kahi ʻikepili nui o nā kiʻi i hōʻailona ʻia. A laila, hiki iā ResNet ke wānana i ka papa o nā kiʻi i ʻike ʻole ʻia.
Hiki ke hoʻohana ʻia ʻo ResNet no nā hana ʻike mea e like me ka ʻimi ʻana i nā mea ma nā kiʻi. Hiki iā mākou ke hana i kēia ma ka hoʻomaʻamaʻa mua ʻana i kahi kumu hoʻohālike ResNet ma kahi hōʻiliʻili o nā kiʻi i hōʻailona ʻia me nā pahu hoʻopaʻa mea. A laila, hiki iā mākou ke hoʻohana i ke kumu hoʻohālike i aʻo ʻia e ʻike i nā mea i nā kiʻi hou.
Hiki iā mākou ke hoʻohana i ResNet no nā hana hoʻokaʻawale semantic. No laila, hiki iā mākou ke hāʻawi i kahi lepili semantic i kēlā me kēia pika i kahi kiʻi.
Inception
ʻO ka hoʻomaka ʻana he kumu hoʻonaʻauao hohonu hiki ke ʻike i nā mea ma nā kiʻi. Ua hoʻolaha ʻo Google iā ia i ka makahiki 2014, a nānā ʻo ia i nā kiʻi o nā ʻano nui me ka hoʻohana ʻana i nā papa he nui. Me Inception, hiki i kāu kumu hoʻohālike ke hoʻomaopopo pololei i ke kiʻi.
He mea hana ikaika ʻo TensorFlow no ka hana ʻana a me ka holo ʻana i nā hiʻohiʻona Inception. Hāʻawi ia i kahi kiʻekiʻe kiʻekiʻe a me ka mea hoʻohana-friendly interface no ka hoʻomaʻamaʻa ʻana i nā pūnaewele neural. No laila, ʻo Inception kahi hiʻohiʻona maʻalahi e noi no nā mea hoʻomohala.
Hoʻokomo i ka Inception
Hiki iā ʻoe ke hoʻouka iā Inception ma ke kākau ʻana i kēia laina code.
from tensorflow.keras.applications import InceptionV3
Nā ʻāpana o ka hoʻomaka ʻana
Hiki ke hoʻohana ʻia ke kumu hoʻohālike no ka unuhi ʻana i nā hiʻohiʻona i loko haʻawina hohonu nā hiʻohiʻona e like me Generative Adversarial Networks (GANs) a me Autoencoders.
Hiki ke hoʻoponopono maikaʻi ʻia ke kumu hoʻohālike no ka ʻike ʻana i nā ʻano kikoʻī. Eia kekahi, hiki iā mākou ke ʻike i kekahi mau maʻi i nā noi kiʻi lāʻau e like me X-ray, CT, a i ʻole MRI.
Hiki ke hoʻoponopono maikaʻi ʻia ke kumu hoʻohālike no ka nānā ʻana i ka maikaʻi o ke kiʻi. Hiki iā mākou ke noʻonoʻo inā he kiʻi ʻaʻaʻa a ʻaʻaʻa paha.
Hiki ke hoʻohana ʻia ka hoʻomaka ʻana no nā hana loiloi wikiō e like me ka nānā ʻana i nā mea a me ka ʻike hana.
BERT
ʻO BERT (Bidirectional Encoder Representations from Transformers) he kumu hoʻohālike pūnaewele neural i hoʻomohala mua ʻia e Google. Hiki iā mākou ke hoʻohana iā ia no nā ʻano hana hoʻoponopono ʻōlelo kūlohelohe. Hiki ke ʻokoʻa kēia mau hana mai ka hoʻokaʻawale kikokikona a i ka pane ʻana i nā nīnau.
Kūkulu ʻia ʻo BERT ma luna o ka hoʻolālā transformer. No laila, hiki iā ʻoe ke mālama i ka nui o ka hoʻokomo kikokikona i ka wā e hoʻomaopopo ai i nā pilina huaʻōlelo.
He kumu hoʻohālike mua ʻo BERT i hiki iā ʻoe ke hoʻohui i nā noi TensorFlow.
Loaʻa iā TensorFlow kahi hiʻohiʻona BERT i hoʻomaʻamaʻa mua ʻia a me kahi hōʻiliʻili o nā pono no ka hoʻoponopono maikaʻi ʻana a me ka hoʻopili ʻana iā BERT i nā hana like ʻole. No laila, hiki iā ʻoe ke hoʻohui maʻalahi i ka hiki ke hoʻoponopono ʻōlelo kūlohelohe o BERT.
Ke hoʻokomo nei iā BERT
Ke hoʻohana nei i ka luna hoʻokele pip, hiki iā ʻoe ke hoʻokomo iā BERT ma TensorFlow:
pip install tensorflow-gpu==2.2.0 # This installs TensorFlow with GPU support
pip install transformers==3.0.0 # This installs the transformers library, which includes BERT
Hiki ke hoʻokomo maʻalahi ka mana CPU o TensorFlow ma ke pani ʻana i ka tensorflow-gpu me ka tensorflow.
Ma hope o ka hoʻokomo ʻana i ka waihona, hiki iā ʻoe ke hoʻokomo i ke kumu hoʻohālike BERT a hoʻohana iā ia no nā hana NLP like ʻole. Eia kekahi laʻana code no ka hoʻoponopono maikaʻi ʻana i ke kumu hoʻohālike BERT ma kahi pilikia hoʻokaʻawale kikokikona, no ka laʻana:
from transformers import BertForSequenceClassification
# Load the pre-trained BERT model
model = BertForSequenceClassification.from_pretrained("bert-base-uncased")
# Fine-tune the model on your text classification task
model.fit(training_data, labels)
# Make predictions on new data
predictions = model.predict(test_data)
Nā wahi hoʻohana o BERT
Hiki iā ʻoe ke hana i nā hana wehewehe kikokikona. Eia kekahi laʻana, hiki ke hoʻokō kālailai manaʻo, hoʻokaʻawale kumuhana, a me ka ʻike spam.
Loaʻa iā BERT kahi ʻIke ʻIke ʻia (NER) hiʻona. No laila, hiki iā ʻoe ke ʻike a hoʻopaʻa inoa i nā mea i loko o ka kikokikona e like me nā kānaka a me nā hui.
Hiki ke hoʻohana ʻia e pane i nā nīnau ma muli o kahi pōʻaiapili, e like me ka ʻenekini huli a i ʻole ka noi chatbot.
Pono paha ʻo BERT no ka unuhi ʻōlelo e hoʻonui i ka pololei o ka unuhi ʻana i ka mīkini.
Hiki ke hoʻohana ʻia ʻo BERT no ka hōʻuluʻulu kikokikona. No laila, hiki iā ia ke hāʻawi i kahi hōʻuluʻulu kūpono o nā palapala kikokikona lōʻihi.
DeepVoice
Ua hana ʻo Baidu Research i DeepVoice, a ʻ -lelo-a-ʻōlelo hoʻohālike synthesis.
Ua hana ʻia me ka TensorFlow framework a aʻo ʻia ma kahi hōʻiliʻili nui o ka ʻikepili leo.
Hoʻopuka ʻo DeepVoice i ka leo mai ka hoʻokomo kikokikona. Hiki iā DeepVoice ke hoʻohana i nā ʻenehana aʻo hohonu. He kumu hoʻohālike pili pūnaewele neural.
No laila, kānana ʻo ia i ka ʻikepili hoʻokomo a hoʻopuka i ka ʻōlelo me ka hoʻohana ʻana i ka nui o nā papa o nā nodes pili.
Ke hoʻokomo nei i DeepVoice
!pip install deepvoice
ʻOkoʻa;
# Clone the DeepVoice repository
!git clone https://github.com/r9y9/DeepVoice3_pytorch.git
%cd DeepVoice3_pytorch
!pip install -r requirements.txt
Nā Ares o ka hoʻohana ʻana o DeepVoice
Hiki iā ʻoe ke hoʻohana i DeepVoice e hana i ka ʻōlelo no nā mea kōkua pilikino e like me Amazon Alexa a me Google Assistant.
Eia kekahi, hiki ke hoʻohana ʻia ʻo DeepVoice e hana i ka haʻiʻōlelo no nā mea leo leo e like me nā ʻōlelo akamai a me nā ʻōnaehana home automation.
Hiki i ka DeepVoice ke hana i leo no nā noi hoʻokele haʻiʻōlelo. Hiki ke kōkua i nā poʻe maʻi me nā pilikia ʻōlelo e hoʻomaikaʻi i kā lākou ʻōlelo.
Hiki ke hoʻohana ʻia ʻo DeepVoice e hana i haʻiʻōlelo no nā mea hoʻonaʻauao e like me nā puke leo a me nā polokalamu aʻo ʻōlelo.
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