AR/ 01

Open to ML & Data opportunities

ALIKHANRAKHYMZHAN

Applied ML Engineer

I build practical systems across deep learning, NLP, recommendation systems, and computer vision.

View projects→ Download CV↓

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Deep Learning Lab

A neural network from scratch with NumPy, including backpropagation, regularization, dropout, and numerical gradient checking.

87.5%test accuracy
2.0e−10gradient error
Repository ↗
  1. DATA
  2. NUMPY NN
  3. GRAD CHECK
  4. API
NUMPY NEURAL NETWORK
Two-layer neural network
DECISION BOUNDARY / SPIRAL DATASET

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ShadowCoach

A browser-based boxing practice system using on-device pose estimation, temporal attempt capture, and rule-based technique feedback.

100labelled clips
51.9%micro-F1
Live product ↗Repository ↗
Right cross movement sequenceSeven front-facing three-dimensional landmark poses from guard through impact and back to guard.
LIVE POSE / LANDMARKS00:00 / 00:08
Animated pose-estimation preview

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NU Club Finder

A hybrid ranking baseline combining semantic similarity from Sentence Transformer embeddings with categorical interest overlap.

150+organizations
70 / 30hybrid baseline
Repository ↗
  1. QUERY
  2. EMBEDDING
  3. HYBRID SCORE
  4. TOP 5
Hybrid recommendation embedding space
TOP 5 RESULTS / HYBRID
  1. 1
  2. 2
  3. 3
  4. 4
  5. 5

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Profile / Learning

My academic background and ongoing learning journey.

University

Nazarbayev UniversityB.S. Computer Science · 2024—2028
Relevant coursework

Additional learning

nFactorial SchoolData Science · Silver
DeepLearning.AINeural Networks and Deep Learning

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Contact

Have an ML problem worth exploring?

EMAILGITHUBLINKEDINCV