Data Sayenzi Yevanotanga
1. Sentiment Analysis (Sentiment Analysis kuburikidza neChinyorwa)
Tarisa uone kuzara kweData Sayenzi chirongwa chekushandisa uchishandisa sosi kodhi - .
Sentiment Analysis (Sentiment Analysis) iongororo yemazwi ekuona manzwiro nemafungiro, anogona kuva akanaka kana akaipa. Iri imhando yemhando umo makirasi anogona kuve mabhinari (akanaka uye asina kunaka) kana mazhinji (anofara, akatsamwa, anosuwa, akashata ...). Tichashandisa chirongwa ichi cheData Science muR uye tichashandisa dataset mu "janeaustenR" package. Tichashandisa maduramazwi echinangwa senge AFINN, bing uye loughran, kuita kubatana kwemukati, uye pakupedzisira tichagadzira gore rezwi kuratidza mhedzisiro.
Π―Π·ΡΠΊ: R
Dataset/Package: janeaustenR
Chinyorwa chakaturikirwa nerutsigiro rweEDISON Software, iyo , pamwe chete .
2. Fake News Detection
Tora hunyanzvi hwako kune inotevera nhanho nekushanda paData Science chirongwa chevanotanga - .
Nhau dzemanyepo inhau yenhema inoparadzirwa kuburikidza nesocial media uye mamwe ma media epamhepo kuzadzisa zvinangwa zvezvematongerwo enyika. Mune ino Data Science chirongwa zano, isu tichashandisa Python kuvaka modhi inogona kunyatsoona kuti nyaya yenhau ndeyechokwadi here kana kuti manyepo. Isu tichagadzira TfidfVectorizer uye toshandisa PassiveAggressiveClassifier kuisa nhau mu "chaiyo" uye "yekunyepedzera". Isu tichashandisa dataset yechimiro 7796 Γ 4 uye tomhanyisa zvese muJupyter Lab.
Π―Π·ΡΠΊ: Python
Dataset/Package: news.csv
3. Kuona chirwere cheParkinson
Famba kumberi neData Science Project Idea yako - .
Tatanga kushandisa Data Science kuvandudza hutano uye masevhisi - kana tikakwanisa kufanotaura chirwere padanho rekutanga, isu tichava nezvakawanda zvakanaka. Saka, mune ino Data Science chirongwa zano, isu tichadzidza nzira yekuona chirwere cheParkinson tichishandisa Python. Icho chirwere cheurourodegenerative, chinofambira mberi chepakati tsinga system chinokanganisa kufamba uye chinokonzera kudedera uye kuoma. Inobata dopamine-inobudisa neurons muuropi, uye gore negore, inobata vanhu vanopfuura mamiriyoni e1 muIndia.
Π―Π·ΡΠΊ: Python
Dataset/Package: UCI ML Parkinsons dataset
Data Science mapurojekiti epakati kuomarara
4. Kutaura Emotion Recognition
Tarisa uone kuitwa kwakazara kweiyo Data Science muenzaniso chirongwa - .
Ngatidzidzei kushandisa maraibhurari akasiyana. Iyi Data Sayenzi purojekiti inoshandisa librosa kucherechedzwa kwekutaura. SER ndiyo nzira yekuziva manzwiro evanhu uye maitiro anobata kubva pakutaura. Sezvo isu tinoshandisa toni nenzwi kuratidza manzwiro nemanzwi edu, SER yakakosha. Asi sezvo manzwiro ari ega, odhiyo annotation ibasa rakaoma. Isu tichashandisa mfcc, chroma uye mel mabasa uye tinoshandisa iyo RAVDESS dataset yekuzivikanwa manzwiro. Isu tichagadzira MLPC classifier yeiyi modhi.
Π―Π·ΡΠΊ: Python
Dataset/Package: RAVDESS dataset
5. Gender uye Age Detection
Kufadza vashandirwi neazvino Data Science chirongwa - .
Iyi inonakidza Data Science nePython. Uchishandisa mufananidzo mumwe chete, iwe uchadzidza kufanotaura murume kana zera uye zera. Mune izvi tichakuzivisa iwe kuComputer Vision nemisimboti yayo. Tichavaka uye achashandisa mamodheru akadzidziswa naTal Hassner naGil Levy pane Adience dataset. Tiri munzira tichashandisa mamwe .pb, .pbtxt, .prototxt uye .caffemodel mafaira.
Π―Π·ΡΠΊ: Python
Dataset/Package: Adience
6. Uber Data Analysis
Tarisa uone kuzara kweData Sainzi purojekiti yekumisikidzwa nekodhi kodhi - .
Iyi ipurojekiti yekuona data ine ggplot2 umo isu tichashandisa R nemaraibhurari ayo uye nekuongorora akasiyana ma paramita. Isu tichashandisa iyo Uber Pickups New York City dhata uye kugadzira zviono zvenguva dzakasiyana dzegore. Izvi zvinotitaurira kuti nguva inokanganisa sei kufamba kwevatengi.
Π―Π·ΡΠΊ: R
Dataset/Package: Uber Pickups muNew York City dataset
7. Mutyairi Kubatwa nehope
Kuvandudza hunyanzvi hwako nekushanda paPamusoro Data Science Project - .
Kutyaira wakatsikitsira kune ngozi zvikuru, uye tsaona dzinoda kusvika chiuru dzinoitika gore negore nekuda kwevatyairi vanorara vachityaira. Muchirongwa ichi chePython, isu tichagadzira sisitimu inogona kuona vatyairi vane hope uye zvakare kuvazivisa nechiratidzo chekuteerera.
Ichi chirongwa chinoitwa uchishandisa Keras uye OpenCV. Isu tichashandisa OpenCV yekuona kumeso uye ziso uye neKeras isu tichaisa ziso mamiriro (Kuvhura kana Kuvharwa) tichishandisa yakadzika neural network matekiniki.
8. Chatbot
Gadzira Chatbot nePython uye tora nhanho kumberi mubasa rako - .
Chatbots chikamu chakakosha chebhizinesi. Mabhizinesi mazhinji anofanirwa kupa masevhisi kune vatengi vavo uye zvinoda simba rakawanda, nguva uye simba kuvashandira. Chatbots inogona kushandura yakawanda yekudyidzana kwevatengi vako nekupindura mimwe mibvunzo yakajairika inobvunzwa nevatengi. Kune mhando mbiri dzechatbots: Domain-specific uye Open-domain. A domain-specific chatbot inowanzo shandiswa kugadzirisa rimwe dambudziko. Saka, iwe unofanirwa kuigadzirisa kuti ishande nemazvo mumunda wako. Open-domain chatbots inogona kubvunzwa chero mibvunzo, saka kuvadzidzisa kunoda huwandu hukuru hwe data.
Data set: Chinangwa json faira
Π―Π·ΡΠΊ: Python
Advanced Data Science mapurojekiti
9. Mufananidzo Caption Generator
Tarisa uone kuitwa kwakazara kweprojekiti ine source code - .
Kutsanangura zviri mumufananidzo ibasa riri nyore kuvanhu, asi kumakomputa, chifananidzo chingori nhevedzano yenhamba dzinomiririra kukosha kweruvara rwepixel yega yega. Iri ibasa rakaoma kumakombiyuta. Kunzwisisa zviri mumufananidzo uyezve kugadzira tsananguro mumutauro wechisikigo (seChirungu) nderimwe basa rakaoma. Ichi chirongwa chinoshandisa nzira dzakadzama dzekudzidza umo isu tinoshandisa Convolutional Neural Network (CNN) ine Recurrent Neural Network (LSTM) kugadzira jenareta yetsananguro yemufananidzo.
Data set: Flickr 8K
Π―Π·ΡΠΊ: Python
Framework: Keras
10. Chikwereti Kadhi Kubiridzira Kuona
Ita nepaunogona napo paunenge uchishanda pane yako Data Science project zano - .
Parizvino watanga kunzwisisa matekiniki uye pfungwa. Ngatienderere mberi kune mamwe mapurojekiti esainzi epamusoro data. Muchirongwa ichi tichashandisa R mutauro une algorithms senge , logistic regression, artificial neural network uye gradient inowedzera classifier. Tichashandisa dhatabheti rekuchinjana kwemakadhi kurongedza kutengeserana kwekadhi rechikwereti sehutsotsi kana hwechokwadi. Isu tichavasarudzira mamodheru akasiyana uye kuvaka ma curves ekuita.
Π―Π·ΡΠΊ: R
Dataset/Package: Kadhi Transactions dataset
11. Movie Recommendation System
Dzidza kuitiswa kweakanakisa Data Sayenzi chirongwa chine Source kodhi -
Mune ino Data Science chirongwa, isu tichashandisa R kuita kurudziro yemubhaisikopo kuburikidza nekudzidza muchina. Iyo yekurudziro sisitimu inotumira mazano kune vashandisi kuburikidza nesefa maitiro zvichienderana nezvinodiwa nevamwe vashandisi uye nhoroondo yekubhurawuza. Kana A naB vachida Kumba Ndega, uye B vachida Vasikana Vachirevesa, saka unogona kupa zano A - vangazvifarirawo. Izvi zvinobvumira vatengi kudyidzana nepuratifomu.
Π―Π·ΡΠΊ: R
Dataset/Package: MovieLens dataset
12. Mutengi Segmentation
Kufadza vashandirwi neData Sayenzi chirongwa (kusanganisira sosi kodhi) - .
Mutengi segmentation chinhu chakakurumbira application . Achishandisa clustering, makambani anoona zvikamu zvevatengi kunongedza angangoita mushandisi base. Vanopatsanura vatengi mumapoka zvichienderana neakajairwa hunhu senge murume kana mukadzi, zera, zvido uye mashandisiro emari kuitira kuti vagone kushambadzira zvigadzirwa zvavo kuboka rega rega. Tichashandisa , pamwe nekuona kugoverwa nevarume nezera. Tichazoongorora mari yavo yegore negore uye mazinga emari.
Π―Π·ΡΠΊ: R
Dataset/Package: Mall_Customers dataset
13. Kurongwa kwekenza yemazamu
Tarisa uone kuitwa kwakazara kweData Sayenzi chirongwa muPython - .
Kudzoka kumupiro wekurapa wesainzi yedata, ngatidzidzei kuona gomarara rezamu uchishandisa Python. Tichashandisa IDC_regular dataset kuona invasive ductal carcinoma, rudzi rwegomarara rezamu. Inokura mumigero yemukaka, ichinyura mumazamu ane fibrous kana ane mafuta ari kunze kwenzira. Mune ino data yekuunganidza sainzi chirongwa zano tichashandisa uye raibhurari yeKeras yekuisa mumapoka.
Π―Π·ΡΠΊ: Python
Dataset/Package: IDC_regular
14. Kuzivikanwa kweTraffic Signs
Kuwana kunyatsoita tekinoroji yekuzvityaira neData Science chirongwa open source.
Zvikwangwani zvemumugwagwa nemitemo yemumigwagwa zvakakosha kuti mutyairi wese adzivise tsaona. Kutevera mutemo, iwe unofanirwa kutanga wanzwisisa kuti chiratidzo chemugwagwa chinotaridzika sei. Munhu anofanira kudzidza zvikwangwani zvese zvemumugwagwa asati apihwa rezenisi rekutyaira chero mota. Asi ikozvino nhamba yemotokari dzinozvimiririra iri kukura, uye munguva pfupi iri kutevera munhu haazotyairi motokari akazvimirira. MuRoad Sign Recognition purojekiti, iwe uchadzidza kuti chirongwa chinogona sei kuziva mhando yezviratidzo zvemumugwagwa nekutora mufananidzo sekuisa. Iyo German Traffic Sign Recognition Benchmark (GTSRB) dataset inoshandiswa kugadzira yakadzika neural network kuona kirasi ine chiratidzo chetraffic. Isu zvakare tinogadzira iri nyore GUI yekudyidzana neyekushandisa.
Π―Π·ΡΠΊ: Python
Data set: GTSRB (Chiratidzo Chekuziva Chiratidzo cheTraffic yeGerman)
Verenga zvimwe
Source: www.habr.com