Master feature engineering for machine learning with a practical, hands-on approach, applying techniques from basic feature creation to PCA, imputation, encoding, regularization, and cross-validation using Python code.
Penataan Fitur Langkah demi Langkah: Persiapan Data ML
Data yang Hilang, Skalasi, Ekstraksi Fitur, Seleksi, Teknik Lanjutan & Penataan Fitur Otomatis
Barcha darajalar • 22 Ma'ruzalar • Umrbod kirish
Tasdiqlangan usta o'qituvchi
TREYLER
O'qituvchi bilan tanishing: Dr. Amar Massoud
19 ms
5.0 / 5.0
Global reyting1
Faol talabalarIngliz (Amerika)
99 ta til subtitrlari1 soat 37 daq
Jami tarkibSiz nimani o'rganasiz
Memahami dan menerapkan teknik penataan fitur untuk meningkatkan akurasi model.
Mengidentifikasi dan mengurangi bias, memastikan seleksi fitur yang adil dan etis.
Mengimplementasikan penataan fitur otomatis menggunakan perpustakaan seperti FeatureTools.
Mengakses dan mendokumentasikan versi fitur untuk reproduksi dan kolaborasi.
Kurs mazmuni
10 bo'limlar • 22 ma'ruzalar • 01:37:25 umumiy uzunligiHandling Missing Data
09:03
Learn strategies to handle missing data, from mean, median, and mode imputation to modeling-based approaches like KNN and regression. Apply these to numerical and categorical features, including frequent category imputation.
Feature Transformation
01:57
Explore feature transformation techniques for machine learning, including scaling, normalization, log and power transformations, binning, and one hot encoding for categorical data.
Scaling and Normalization
05:40
Learn to scale and normalize features using standardization to zero mean and unit variance or min-max normalization to 0–1, improving model training on housing data.
Log Transformation, Power Transformation
05:16
Binning Numerical Variables
03:36
One-Hot Encoding vs. Label Encoding
04:07
Compare one-hot encoding and label encoding for transforming categorical data into numerical features, weighing dimensionality against potential ordinal assumptions in different datasets.
Haftalik Oquv Rejasi
Oquv sayohatingizni rejalashtiring
SI vaqtingizga mos shaxsiy jadval yaratadi5 soat/hafta
Talablar
Pemahaman dasar tentang Python dan konsep pembelajaran mesin.
Familiar dengan Pandas dan Scikit-learn.
Pengalaman dasar bekerja dengan dataset disarankan.
Tidak diperlukan pengalaman penataan fitur lanjutan.
Maqsadli auditoriya
Data science enthusiasts looking to deepen their skills in feature engineering.
Beginner and intermediate data scientists aiming to improve model performance.
Machine learning practitioners who want practical, hands-on experience.
Developers interested in ethical AI and responsible data practices.
Ushbu kurs haqida
Buka potensi penuh model mesin Anda dengan kursus komprehensif kami tentang Penataan Fitur. Dirancang untuk penggemar ilmu data, praktisi mesin belajar, dan pengembang, kursus ini mencakup teknik penataan fitur esensial dan lanjutan yang akan meningkatkan kinerja, akurasi, dan interpretabilitas model Anda.
Dari menangani data yang hilang dan transformasi fitur hingga penataan fitur otomatis dengan perpustakaan seperti FeatureTools, Anda akan mempelajari keterampilan untuk membuat fitur yang kuat dan relevan. Temukan teknik kunci seperti skalasi, normalisasi, pengkodean satu-panas, dan ekstraksi fitur. Pahami kapan menerapkan fitur polinomial dan interaksi untuk mengungkap pola yang lebih dalam, serta memanfaatkan fitur berbasis waktu untuk data seri waktu. Kursus ini juga memperkenalkan pertimbangan etis penting, menunjukkan kepada Anda cara menghindari bias, memastikan keadilan, dan meningkatkan interpretabilitas dalam fitur Anda.
Melalui contoh praktis, kasus penggunaan konsisten di dunia nyata, dan kode Python untuk setiap metode, Anda akan memperoleh pengalaman praktis yang dapat Anda terapkan segera. Anda juga akan mempelajari praktik terbaik untuk dokumentasi dan kontrol versi, memastikan fitur Anda terorganisir dan dapat direproduksi. Terakhir, dengan teknik pembelajaran berkesinambungan dan iterasi, Anda dilengkapi untuk menjaga model Anda relevan dan efektif seiring evolusi data.
Baik Anda ingin memperhalus keterampilan penataan fitur atau mengotomatiskan alur kerja Anda, kursus ini menyediakan pengetahuan dan alat untuk membangun model berkinerja tinggi dan etis. Bergabunglah hari ini dan mengambil langkah menuju penguasaan penataan fitur dalam pembelajaran mesin!
Karyera imkoniyatlari va maqsadli kasblar
Amaliy va ishga tayyor ko'nikmalarni egallab, xalqaro miqyosdagi nufuzli lavozimlarga ariza topshiring
Ishga tayyor o'quv dasturi
Ariza topshirishingiz mumkin bo'lgan lavozimlar
AI Solutions Engineer
Data Science Consultant
Machine Learning Practitioner
AI Workflow & Automation Specialist
Taxminiy yillik maosh
$105,000 – $165,000 / yr
Global bozor talabi
Fastest Growing Worldwide (#1)
Siz egallaydigan asosiy ko'nikmalar* Baholar global texnologiya bozori va maosh hisobotlariga asoslangan.
Model Fine-Tuning & Evaluation
Data Pipelines & Vector Analysis
Applied Generative AI Architecture
Predictive Analytics & Deployment
O'qituvchingiz bilan tanishing
Dr. Amar Massoud
Bosh murabbiy
PhD in computer science and IT manager with 36 years technical experience in various fields including IT Security, IT Governance, IT Service Management , Software Development, Project Management, Business Analysis and Software Architecture. I hold 80+ IT certifications such as :
ITIL 4 Master, ITIL 3 Expert
ISO 27001 Auditor, ComptIA Security+, GSEC, CEH, ECSA, CISM, CISSP, CISA
PGMP, MSP
PMP, PMI-ACP, Prince2 Practitioner, Praxis, Scrum Master
COBIT 2019 Implementor, COBIT 5 Assessor/Implementer
TOGAF certified
Lean Specialist, VSM Specialist
PMI RMP, ISO 31000 Risk Manager, ISO 22301 Lead Auditor
PMI-PBA, CBAP
Lean Six Sigma Black Belt, ISO 9001 Implementer
Azure Administrator, Azure DevOps Expert, AWS Practitioner
And many more....
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Tez-tez so'raladigan savollar
Ushbu kurs bo'yicha eng keng tarqalgan savollarga javob toping.
Ha! Upon completing 100% of the course lectures and assignments, you can instantly download your verified digital Certificate of Completion directly from your Lucebra profile.
Technology bo'yicha ko'proq bilib oling
Akkreditatsiyadan o'tgan sertifikatlar, elektron kitoblar va jonli darslar bilan bilimlaringizni oshiring.