Otu n'ime ngwaọrụ ndị ama ama maka ịmepụta ụdị mmụta igwe bụ TensorFlow. Anyị na-eji TensorFlow n'ọtụtụ ngwa na ụlọ ọrụ dị iche iche.
Na post a, anyị ga-enyocha ụfọdụ ụdị TensorFlow AI. N'ihi ya, anyị nwere ike ịmepụta usoro ọgụgụ isi.
Anyị ga-agafekwa usoro nke TensorFlow na-enye maka ịmepụta ụdị AI. Ya mere, ka anyị malite!
Okwu mmalite nke TensorFlow
TensorFlow nke Google bụ isi mmalite mepere emepe ngwa igwe ngwugwu software. Ọ gụnyere ngwaọrụ maka ọzụzụ na ibugharị ụdị igwe eji amụ ihe n'ọtụtụ nyiwe. na ngwaọrụ, yana nkwado maka mmụta miri emi na neural netwọk.
TensorFlow na-enyere ndị mmepe aka ịmepụta ụdị maka ngwa dị iche iche. Nke a gụnyere njirimara onyonyo na ọdịyo, nhazi asụsụ eke, yana ọhụụ kọmputa. Ọ bụ ngwá ọrụ siri ike ma na-agbanwe agbanwe nwere nkwado obodo zuru ebe niile.
Iji tinye TensorFlow na kọmputa gị, ị nwere ike pịnye nke a na windo iwu gị:
pip install tensorflow
Kedu ka ụdị AI si arụ ọrụ?
Ụdị AI bụ usoro kọmputa. Ya mere, ha bu n'obi ime ihe omume ga-achọkarị ọgụgụ isi mmadụ. Ihe onyonyo na imata okwu na ime mkpebi bụ ihe atụ nke ọrụ ndị dị otú ahụ. A na-emepụta ụdị AI na nnukwu datasets.
Ha na-eji usoro mmụta igwe n'iwepụta amụma ma mee omume. Ha nwere ọtụtụ ojiji, gụnyere ụgbọ ala na-anya onwe ya, ndị enyemaka onwe onye, na nyocha ahụike.
Yabụ, kedu ụdị TensorFlow AI a ma ama?
ResNet
ResNet, ma ọ bụ Residual Network, bụ ụdị mgbanwe neural network. Anyị na-eji ya maka nhazi ihe oyiyi na nchọpụta ihe. Ndị na-eme nchọpụta Microsoft mepụtara ya na 2015. Ọzọkwa, a na-amata ya site na iji njikọ ndị fọdụrụnụ.
Njikọ ndị a na-enye ohere ka netwọkụ mụta nke ọma. N'ihi ya, ọ ga-ekwe omume site n'ime ka ozi na-aga n'efu n'etiti ọkwa.
Enwere ike itinye ResNet na TensorFlow site na itinye Keras API. Ọ na-enye ọkwa dị elu, interface enyi na enyi maka ịmepụta na ịzụ netwọkụ akwara.
Ịwụnye ResNet
Mgbe ị wụnyechara TensorFlow, ị nwere ike iji Keras API mepụta ụdị ResNet. TensorFlow gụnyere Keras API, yabụ na ịchọghị ịwụnye ya n'otu n'otu.
Ị nwere ike ibubata ụdị ResNet site na tensorflow.keras.applications. Ma, ị nwere ike họrọ ụdị ResNet iji, dịka ọmụmaatụ:
from tensorflow.keras.applications import ResNet50
Ị nwekwara ike iji koodu na-esonụ iji buo ibu a zụrụ azụ maka ResNet:
model = ResNet50(weights='imagenet')
Site n'ịhọrọ ihe onwunwe gụnyere_top=Ụgha, ị nwekwara ike iji ihe nlereanya ahụ maka ọzụzụ agbakwunyere ma ọ bụ imezigharị dataset omenala gị.
model = ResNet50(weights='imagenet', include_top=False, input_shape=(224, 224, 3))
Mpaghara ojiji nke ResNet
Enwere ike iji ResNet na nhazi onyonyo. Yabụ, ị nwere ike ekewa foto n'ime ọtụtụ otu. Nke mbụ, ịkwesịrị ịzụ ihe nlereanya ResNet na nnukwu dataset nke foto ndị akpọrọ. Mgbe ahụ, ResNet nwere ike ibu amụma klas nke onyonyo a na-ahụbeghị na mbụ.
Enwere ike iji ResNet rụọ ọrụ nchọpụta ihe dị ka ịchọpụta ihe dị na foto. Anyị nwere ike ime nke a site na ibu ụzọ zụọ ihe nlereanya ResNet na nchịkọta foto nke ejiri igbe na-ejikọta ihe. Mgbe ahụ, anyị nwere ike itinye ụdị mmụta mmụta iji mata ihe dị na onyonyo ọhụrụ.
Anyị nwekwara ike iji ResNet maka ọrụ nkewa semantic. Yabụ, anyị nwere ike kenye akara semantic na pikselụ ọ bụla na onyonyo.
inception
Mmalite bụ usoro mmụta miri emi nke nwere ike ịmata ihe dị na onyonyo. Google kwuputara ya na 2014, ọ na-enyocha onyonyo nke nha dị iche iche site na iji ọtụtụ ọkwa. Site na mmalite, ihe nlereanya gị nwere ike ịghọta onyonyo a nke ọma.
TensorFlow bụ ngwá ọrụ siri ike maka ịmepụta na ịgba ọsọ ụdị Inception. Ọ na-enye interface dị elu yana enyi na enyi maka ịzụ netwọkụ akwara. N'ihi ya, Inception bụ ezigbo ihe nlere anya iji tinye maka ndị mmepe.
Ntinye mmalite
Ị nwere ike ịwụnye Inception site na ịpịpụta ahịrị koodu a.
from tensorflow.keras.applications import InceptionV3
Mpaghara ojiji nke mmalite
Enwere ike iji ụdị mmalite mmalite wepụta njirimara na mmụta miri emi ụdị dị ka Generative Adversarial Networks (GANs) na Autoencoders.
Enwere ike idozi ụdị mmalite mmalite nke ọma iji chọpụta àgwà ndị akọwapụtara. Ọzọkwa, anyị nwere ike ịchọpụta nsogbu ụfọdụ na ngwa onyonyo ahụike dịka X-ray, CT, ma ọ bụ MRI.
Enwere ike idozi ụdị mmalite mmalite iji lelee ogo onyonyo. Anyị nwere ike inyocha ma onyonyo ọ na-afụ ụfụ ma ọ bụ cha cha.
Enwere ike iji mmalite maka ọrụ nyocha vidiyo dịka nsochi ihe yana nchọpụta ihe.
BERT
BERT (Nnọchite anya Encoder Bidirectional sitere na Transformers) bụ ụdị netwọkụ akwara azụpụtara nke Google zụrụ. Anyị nwere ike iji ya rụọ ọrụ nhazi asụsụ okike dị iche iche. Ọrụ ndị a nwere ike ịdịgasị iche site na nhazi ederede ruo na ịza ajụjụ.
Ewubere BERT na nhazi ihe nrụzigharị. N'ihi ya, ị nwere ike ijikwa nnukwu ntinye ederede ka ị na-aghọta njikọ okwu.
BERT bụ ụdị a zụrụ azụ nke ị nwere ike itinye n'ime ngwa TensorFlow.
TensorFlow na-agụnye ụdị BERT a zụrụ azụ yana nchịkọta akụrụngwa maka imezi nke ọma na itinye BERT n'ọrụ dị iche iche. Yabụ, ị nwere ike iwekota ngwa ngwa BERT siri ike nhazi asụsụ okike.
Ịwụnye BERT
Iji njikwa ngwugwu pip, ị nwere ike iwunye BERT na 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
Enwere ike itinye ụdị CPU nke TensorFlow ngwa ngwa site na iji tensorflow dochie tensorflow-gpu.
Mgbe ị wụnyechara ọba akwụkwọ, ị nwere ike ibubata ụdị BERT wee jiri ya rụọ ọrụ NLP dị iche iche. Nke a bụ ụfọdụ koodu nlele maka imezigharị ụdị BERT na nsogbu nhazi ederede, dịka ọmụmaatụ:
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)
Mpaghara BERT eji
Ị nwere ike ịrụ ọrụ nhazi ederede. Dịka ọmụmaatụ, ọ ga-ekwe omume imezu echiche nyocha, nhazi isiokwu, na nchọpụta spam.
BERT nwere a Aha Aha Aha Aha (NER) atụmatụ. N'ihi ya, ị nwere ike ịmata ma kpọọ aha ụlọ ọrụ na ederede dịka ndị mmadụ na otu.
Enwere ike iji ya zaa ajụjụ dabere n'otu ọnọdụ, dị ka n'igwe nchọta ma ọ bụ ngwa chatbot.
BERT nwere ike ịba uru maka Ntụgharị Asụsụ iji kwalite izizi ntụgharị asụsụ igwe.
Enwere ike iji BERT maka nchịkọta ederede. N'ihi ya, ọ nwere ike ịnye nchịkọta akwụkwọ dị ogologo, nke bara uru.
DeepVoice
Nyocha Baidu kere DeepVoice, a ederede-to-okwu nhazi usoro.
Ejiri usoro TensorFlow mepụta ya ma zụọ ya na nnukwu nchịkọta data olu.
DeepVoice na-ewepụta olu site na ntinye ederede. DeepVoice na-eme ka o kwe omume site na iji usoro mmụta miri emi. Ọ bụ ihe nlereanya dabere na netwọkụ akwara.
N'ihi ya, ọ na-enyocha data ntinye ma na-ewepụta okwu site na iji ọnụ ọgụgụ buru ibu nke ọnụ ọnụ ejikọrọ.
Ịwụnye DeepVoice
!pip install deepvoice
Nke ozo;
# Clone the DeepVoice repository
!git clone https://github.com/r9y9/DeepVoice3_pytorch.git
%cd DeepVoice3_pytorch
!pip install -r requirements.txt
Ebe eji eme DeepVoice
Ị nwere ike iji DeepVoice mepụta okwu maka ndị enyemaka onwe onye dị ka Amazon Alexa na Google Assistant.
Ọzọkwa, enwere ike iji DeepVoice mepụta okwu maka ngwaọrụ nwere olu dị ka smart ọkà okwu na sistemụ akpaaka ụlọ.
DeepVoice nwere ike ịmepụta olu maka ngwa ọgwụgwọ okwu. Ọ nwere ike inyere ndị ọrịa nwere nsogbu okwu aka imeziwanye okwu ha.
Enwere ike iji DeepVoice mepụta okwu maka ihe nkuzi dịka akwụkwọ ọdịyo na ngwa mmụta asụsụ.
Nkume a-aza