Practices 100 plus ML Interview questions and answers from youtube shorts.
https://www.youtube.com/@learncloudMLGneAiJobTasks/shorts

Ace Your ML Interview with 100+ Essential Questions Covering Algorithms, Models & Real-World Applications!
Covers key ML concepts thoroughly
This set of 200 questions ensures a strong understanding of fundamental and advanced machine learning concepts, from supervised learning to deep learning.
Focuses on algorithms and models
The questions emphasize important ML algorithms, optimization techniques, and various models like decision trees, neural networks, and ensemble learning.
Includes real-world ML applications
Practical applications of ML in industries such as healthcare, finance, and robotics are covered to help understand how ML is used in real scenarios.
Prepares for technical ML interviews
These questions are designed to help candidates tackle ML interviews by covering theoretical knowledge, coding challenges, and problem-solving techniques.
Video Title URL
120-Self-Organizing Maps https://www.youtube.com/shorts/QHpvMp_TcAc
119-AutoML https://www.youtube.com/shorts/zUtPLPO0gxk
118-Sparse Learning https://www.youtube.com/shorts/wnGyspDyY9M
117-Adversarial Learning https://www.youtube.com/shorts/ptsviWnVHCo
116-Gradient Boosting https://www.youtube.com/shorts/b0-4vLZ1WxA
115-Transformers https://www.youtube.com/shorts/1IusFAFOb9c
114-Neural Architecture Search https://www.youtube.com/shorts/otsVo5pMqn4
113-Reinforcement Learning https://www.youtube.com/shorts/yNG84igrEGc
112-Transfer Learning https://www.youtube.com/shorts/r20XyagPAOk
111-Bayesian Optimization https://www.youtube.com/shorts/RrQy7CmZDPE
110-Active Learning https://www.youtube.com/shorts/U7Ke35TMXtU
109-Federated Learning https://www.youtube.com/shorts/xcKYv6h0Kwo
108-Model Compression https://www.youtube.com/shorts/eq9YYNoAfxk
107-Continual Learning https://www.youtube.com/shorts/s9t8sa5hc_Y
106-Meta Learning https://www.youtube.com/shorts/F_0ZbXdoyC8
105-Multi-Task Learning https://www.youtube.com/shorts/WEO8u9R1y1s
104-Contrastive Learning https://www.youtube.com/shorts/qBEwf0qJa2w
103-Self-Supervised Learning https://www.youtube.com/shorts/-HvB350HONY
102-Few-Shot Learning https://www.youtube.com/shorts/vR_gZYlVIv8
101-Zero-Shot Learning https://www.youtube.com/shorts/09Tak9uxN5I
100-Quantum ML Benefits https://www.youtube.com/shorts/Bm2BUxU1Mfs
99-Continual Learning https://www.youtube.com/shorts/d2U9hpoflWc
98-Transformer Weaknesses https://www.youtube.com/shorts/gr-V5LnmJr4
97-Attention Mechanisms https://www.youtube.com/shorts/ln0EE3UdldQ
96-Few-Shot Learning https://www.youtube.com/shorts/I6_Wqlyp8hI
100-Quantum ML Benefits https://www.youtube.com/shorts/IxOT7p97H_w
95-Multi-Task Learning https://www.youtube.com/shorts/anpXo_p0dI8
94-Latent Variable Models https://www.youtube.com/shorts/D3NaLyo6Ps8
93-Autoencoder Overfitting https://www.youtube.com/shorts/m9SvqJ6gw4A
93-Autoencoder Overfitting https://www.youtube.com/shorts/ptoksIKhW4A
92-Dynamic Graph Learning https://www.youtube.com/shorts/iRCTtifO0rU
91-Semi-Supervised Learning https://www.youtube.com/shorts/VgQmi0hDvg0
90-Anomaly Explanation https://www.youtube.com/shorts/mz_tVVrmBmo
89-Sensor Noise https://www.youtube.com/shorts/quL-5BZOhpo
88-Labeling Costs https://www.youtube.com/shorts/sGTgWJ1YXqI
87-Model Compression https://www.youtube.com/shorts/Af40LRjWRh4
86-Causal Inference https://www.youtube.com/shorts/WzJ82uJQ15E
85-Bias in RL https://www.youtube.com/shorts/cIYgnbsxg48
84-Data Imputation Errors https://www.youtube.com/shorts/Py6D8dxAZNI
83-Edge AI Challenges https://www.youtube.com/shorts/qO49vI0Yq6Y
82-Feature Scaling https://www.youtube.com/shorts/BFeLHi9Zi64
81-Neural Architecture Search https://www.youtube.com/shorts/DsRrrhHc7d8
80-Explainability in RL https://www.youtube.com/shorts/zGgCWX6_8Cg
79-Hybrid ML Models https://www.youtube.com/shorts/yd20OvThI0g
78-Federated Learning https://www.youtube.com/shorts/R-OxCrSh4w0
77-Sparse Data Handling https://www.youtube.com/shorts/NigBwCRA75E
76-Quantum ML https://www.youtube.com/shorts/PhlvD5tCoj4
75-Graph Neural Networks https://www.youtube.com/shorts/d6YI88hfUI0
Title URL
171-YOLO Algorithm https://www.youtube.com/shorts/N0hyoEGZvk0
170-Haar Cascades https://www.youtube.com/shorts/Izwsd-OHx8U
170-Haar Cascades https://www.youtube.com/shorts/S2MAkVJlcio
169-Mean Squared Error https://www.youtube.com/shorts/BRVAiAL85FQ
168-Cross-Entropy Loss https://www.youtube.com/shorts/XnTLtlyDGR8
167-Hinge Loss https://www.youtube.com/shorts/Xq3-71itb5g
166-Perceptron https://www.youtube.com/shorts/Me-fPFdww0Q
165-Self-Attention https://www.youtube.com/shorts/MyD62YNMqB4
164-Neural Style Transfer https://www.youtube.com/shorts/lxXRPaWc5nc
163-Style Transfer https://www.youtube.com/shorts/rCjKXusZUWI
162-GAN Loss Functions https://www.youtube.com/shorts/hFqKR-rxtjc
161-Denoising Autoencoders https://www.youtube.com/shorts/vsCb0Jghe0k
160-Variational Autoencoders https://www.youtube.com/shorts/Lka18dxR-zw
159-Autoencoders https://www.youtube.com/shorts/MPHDmaFb_N0
158-Siamese Networks https://www.youtube.com/shorts/4g2dFmovtUU
157-DropConnect https://www.youtube.com/shorts/WpTDcNPWOa8
156-Greedy Search https://www.youtube.com/shorts/cYbRdcbeM2o
155-Beam Search https://www.youtube.com/shorts/YVhRCnXglg0
154-Recurrent Neural Networks https://www.youtube.com/shorts/8zRV7uS2BME
153-Early Stopping https://www.youtube.com/shorts/EjL_l6LtgwQ
152-Exploding Gradient https://www.youtube.com/shorts/S5X6IrFM3Eg
150-GRUs https://www.youtube.com/shorts/iZigakVDev0
149-LSTMs https://www.youtube.com/shorts/NDn0fWVSaVU
148-GPT Models https://www.youtube.com/shorts/cPAwxO66UD8
146-BERT https://www.youtube.com/shorts/TE0a1N_tI-4
145-GloVe https://www.youtube.com/shorts/VdO8dOBFtno
144-FastText https://www.youtube.com/shorts/RLZmAkB-zFI
143-Word Embeddings https://www.youtube.com/shorts/u8A7j988RmI
142-U-MAP https://www.youtube.com/shorts/bO30fxv2pC4
141-T-SNE https://www.youtube.com/shorts/nERgTFJ_oVg
147-XLNet https://www.youtube.com/shorts/vYuzxj9MJu8
140-Silhouette Score https://www.youtube.com/shorts/kvgtdoLgh2w
139-Hierarchical Clustering https://www.youtube.com/shorts/sYHshl1v3jw
138-Naive Bayes https://www.youtube.com/shorts/mmJv53jQrF8
137-Polynomial Regression https://www.youtube.com/shorts/B_d90SEHz-E
136-Support Vector Machines https://www.youtube.com/shorts/NCwy-rSboE4
135-Random Forest https://www.youtube.com/shorts/c-9KEmbJ7So
134-Decision Trees https://www.youtube.com/shorts/-F5g-FHdr1A
133-Weight Pruning https://www.youtube.com/shorts/dqaS-8NOgaE
132-Capsule Networks https://www.youtube.com/shorts/Cg0sYr8tz44
131-Attention Mechanisms https://www.youtube.com/shorts/iJxBOlI_Uo8
140-Silhouette Score https://www.youtube.com/shorts/FNkImL82VtY
130-GANs https://www.youtube.com/shorts/11Jnw_OG-uI
129-Explainable AI (XAI) https://www.youtube.com/shorts/GugaOx7iAAI
128-Dropout Regularization https://www.youtube.com/shorts/j4b0rAZdZtU
127-Batch Normalization https://www.youtube.com/shorts/lSzo65d7gRg
126-Data Augmentation https://www.youtube.com/shorts/BY0yd7WbuzQ
125-Hyperparameter Tuning https://www.youtube.com/shorts/nysUfD0mr58
124-Catastrophic Forgetting https://www.youtube.com/shorts/79rBNNx7zSc
123-Incremental Learning https://www.youtube.com/shorts/FWCgrN75TGc
122-Manifold Learning https://www.youtube.com/shorts/Ev_f_RI1Pwo
121-Graph Neural Networks https://www.youtube.com/shorts/ED4EJnEw6Vk
120-Self-Organizing Maps https://www.youtube.com/shorts/QHpvMp_TcAc
119-AutoML https://www.youtube.com/shorts/zUtPLPO0gxk
118-Sparse Learning https://www.youtube.com/shorts/wnGyspDyY9M
117-Adversarial Learning https://www.youtube.com/shorts/ptsviWnVHCo
116-Gradient Boosting https://www.youtube.com/shorts/b0-4vLZ1WxA
115-Transformers https://www.youtube.com/shorts/1IusFAFOb9c
114-Neural Architecture Search https://www.youtube.com/shorts/otsVo5pMqn4
113-Reinforcement Learning https://www.youtube.com/shorts/yNG84igrEGc
112-Transfer Learning https://www.youtube.com/shorts/r20XyagPAOk
111-Bayesian Optimization https://www.youtube.com/shorts/RrQy7CmZDPE
110-Active Learning https://www.youtube.com/shorts/U7Ke35TMXtU
109-Federated Learning https://www.youtube.com/shorts/xcKYv6h0Kwo
108-Model Compression https://www.youtube.com/shorts/eq9YYNoAfxk
107-Continual Learning https://www.youtube.com/shorts/s9t8sa5hc_Y
106-Meta Learning https://www.youtube.com/shorts/F_0ZbXdoyC8
105-Multi-Task Learning https://www.youtube.com/shorts/WEO8u9R1y1s
104-Contrastive Learning https://www.youtube.com/shorts/qBEwf0qJa2w
103-Self-Supervised Learning https://www.youtube.com/shorts/-HvB350HONY
102-Few-Shot Learning https://www.youtube.com/shorts/vR_gZYlVIv8
101-Zero-Shot Learning https://www.youtube.com/shorts/09Tak9uxN5I
100-Quantum ML Benefits https://www.youtube.com/shorts/Bm2BUxU1Mfs
99-Continual Learning https://www.youtube.com/shorts/d2U9hpoflWc
98-Transformer Weaknesses https://www.youtube.com/shorts/gr-V5LnmJr4
97-Attention Mechanisms https://www.youtube.com/shorts/ln0EE3UdldQ
96-Few-Shot Learning https://www.youtube.com/shorts/I6_Wqlyp8hI
100-Quantum ML Benefits https://www.youtube.com/shorts/IxOT7p97H_w
95-Multi-Task Learning https://www.youtube.com/shorts/anpXo_p0dI8
94-Latent Variable Models https://www.youtube.com/shorts/D3NaLyo6Ps8
93-Autoencoder Overfitting https://www.youtube.com/shorts/m9SvqJ6gw4A
93-Autoencoder Overfitting https://www.youtube.com/shorts/ptoksIKhW4A
92-Dynamic Graph Learning https://www.youtube.com/shorts/iRCTtifO0rU
91-Semi-Supervised Learning https://www.youtube.com/shorts/VgQmi0hDvg0
90-Anomaly Explanation https://www.youtube.com/shorts/mz_tVVrmBmo
89-Sensor Noise https://www.youtube.com/shorts/quL-5BZOhpo
88-Labeling Costs https://www.youtube.com/shorts/sGTgWJ1YXqI
87-Model Compression https://www.youtube.com/shorts/Af40LRjWRh4
86-Causal Inference https://www.youtube.com/shorts/WzJ82uJQ15E
85-Bias in RL https://www.youtube.com/shorts/cIYgnbsxg48
84-Data Imputation Errors https://www.youtube.com/shorts/Py6D8dxAZNI
83-Edge AI Challenges https://www.youtube.com/shorts/qO49vI0Yq6Y
82-Feature Scaling https://www.youtube.com/shorts/BFeLHi9Zi64
81-Neural Architecture Search https://www.youtube.com/shorts/DsRrrhHc7d8
80-Explainability in RL https://www.youtube.com/shorts/zGgCWX6_8Cg
79-Hybrid ML Models https://www.youtube.com/shorts/yd20OvThI0g
78-Federated Learning https://www.youtube.com/shorts/R-OxCrSh4w0
77-Sparse Data Handling https://www.youtube.com/shorts/NigBwCRA75E
76-Quantum ML https://www.youtube.com/shorts/PhlvD5tCoj4
75-Graph Neural Networks https://www.youtube.com/shorts/d6YI88hfUI0
74-Weak Labeling https://www.youtube.com/shorts/d1vakQF4MnI
73-Imbalanced Data Metrics https://www.youtube.com/shorts/z0zQ10sgziY
72-Ensemble Learning https://www.youtube.com/shorts/XwaM3kXNSKA
71-AutoML Costs https://www.youtube.com/shorts/7FBFzEN-uqw
70-Contrastive Learning https://www.youtube.com/shorts/fn0A9JOLspo
80-Explainability in RL https://www.youtube.com/shorts/0TN3HRWSeKY
69-Zero-Shot Learning https://www.youtube.com/shorts/eHE91VCtmiE
68-Self-Supervised Learning https://www.youtube.com/shorts/rh3ERxZ1Zus
67-Time-Series Forecasting https://www.youtube.com/shorts/dNj8KztBF2Q
66-Sequence Data Errors https://www.youtube.com/shorts/1-OySJUNyVI
65-Bias in Word Embeddings https://www.youtube.com/shorts/DGk5X9m7Sks
64-Low Precision in NLP https://www.youtube.com/shorts/uOxdCwfz_Qw
63-One-Hot Encoding Errors https://www.youtube.com/shorts/hHObTlvDKuI
62-Importance of Normalization https://www.youtube.com/shorts/3sMT-oe56fE
61-Model Drift https://www.youtube.com/shorts/z8qATNn5yQk
60-Overuse of Deep Learning https://www.youtube.com/shorts/Nmeg1oEMfgA
59-Transfer Learning Challenges https://www.youtube.com/shorts/wkUnhEQbF1c
58-Data Augmentation Optimization https://www.youtube.com/shorts/5idltqc6EBo
57-Vanishing Gradients https://www.youtube.com/shorts/9JZG-w1TSxU
56-Feature Correlation Issues https://www.youtube.com/shorts/FW6CZICl5Ic
55-Default Parameter Risks https://www.youtube.com/shorts/UOfn1ttIYqs
54-Inconsistent Data Preprocessing https://www.youtube.com/shorts/bJTWZWeeD7c
53-Insufficient Training Data https://www.youtube.com/shorts/tkvr2wqMBxs
52-Activation Function Choice https://www.youtube.com/shorts/twoiJeVN0Ok
51-Hyperparameter Overfitting https://www.youtube.com/shorts/XHjq7Usk_uk
50-Feature Drift in Time Series https://www.youtube.com/shorts/vYyPJmD786s
49-Data Labeling Inconsistencies https://www.youtube.com/shorts/K8tw_zo1HO0
48-Deploying Models on Edge Devices https://www.youtube.com/shorts/V428L6AEQ38
47-Incorrect Evaluation Metrics https://www.youtube.com/shorts/PIEnfP8fP2c
46-Explainability in Deep Learning https://www.youtube.com/shorts/hhkZvryRSeU
45-ML Model Staleness https://www.youtube.com/shorts/R-iCCJ5FMDs
44-Ethical Bias in AI https://www.youtube.com/shorts/Oa_tqg5yLCs
43-ML Model Versioning Problems https://www.youtube.com/shorts/OnypJjhxnXU
42-Object Detection Accuracy Issues https://www.youtube.com/shorts/NbeEEA6TR0U
41-TensorFlow/PyTorch Compatibility Issues https://www.youtube.com/shorts/HZ2Hs9AZANs
40-Poor GAN Convergence https://www.youtube.com/shorts/X3fhYw4I2oE
39-Adversarial Attack Vulnerabilities https://www.youtube.com/shorts/tdnwHyA4TbI
38-Model Pruning Inefficiency https://www.youtube.com/shorts/WzL_2NNNBU0
37-Federated Learning Privacy Concerns https://www.youtube.com/shorts/CFs7vB6qv3g
36-Transfer Learning Challenges https://www.youtube.com/shorts/bccY3pNkdzM
35-Weak Model Regularization https://www.youtube.com/shorts/wx4F_Uk3zFA
34-Hyperparameter Grid Search Limits https://www.youtube.com/shorts/MVetVXKNEUE
33-Class Imbalance in Predictions https://www.youtube.com/shorts/wzcmPDF0V1s
32-Catastrophic Forgetting in Models https://www.youtube.com/shorts/LjldbqH23h0
31-Concept Drift in Production https://www.youtube.com/shorts/014IbidGGaY
30-Model Serving Latency https://www.youtube.com/shorts/0czQqYRiN-U
29-Mismatched Label Encoding https://www.youtube.com/shorts/VkShSWBIAxU
28-NLP Tokenization Errors https://www.youtube.com/shorts/NrYS_OlniZI
27-Reinforcement Learning Instability https://www.youtube.com/shorts/lpEA1XkQfYU
26-Model Interpretability Issues https://www.youtube.com/shorts/LchLyQ0_6sU
25-Anomaly Detection Failures https://www.youtube.com/shorts/Jo9hPUB5Pgk
24-Training Data Storage Constraints https://www.youtube.com/shorts/pmb65PdoEdI
23-Inconsistent Cross-Validation Results https://www.youtube.com/shorts/QJ79omd6mn0
22-Large Model Deployment Issues https://www.youtube.com/shorts/B5tAE_YYGkQ
21-Computational Cost of Training https://www.youtube.com/shorts/qwVuXwcAtUU
20-ML Pipeline Failures https://www.youtube.com/shorts/prUd9v5nr7g
19-Poor Data Preprocessing https://www.youtube.com/shorts/Ht5ySJ_Woe4
18-Scaling Issues in ML Models https://www.youtube.com/shorts/qODb4VKQuWk
17-Feature Selection Problems https://www.youtube.com/shorts/xrss7YdSSF4
16-Low Model Accuracy https://www.youtube.com/shorts/4TyyfDd0EjQ
15-Model Explainability Challenges https://www.youtube.com/shorts/JgxMmEEWlyg
14-Data Drift Detection https://www.youtube.com/shorts/A5IuFpZTj8E
13-Missing Data Issues https://www.youtube.com/shorts/N7fQX3Wqoz4
12-Noisy Data Handling https://www.youtube.com/shorts/KdZ5u67hX0A
11-Outdated Training Data https://www.youtube.com/shorts/qzsY1-KxyJE
10-Poor Model Generalization https://www.youtube.com/shorts/AqQ9itlnuFQ
9-Hyperparameter Tuning Complexity https://www.youtube.com/shorts/r4szMKQZ2NE
8-Feature Engineering Errors https://www.youtube.com/shorts/KHoR_CpI0h4
7-Imbalanced Dataset https://www.youtube.com/shorts/cjBWB7MvCJo
6-Biased Model Predictions https://www.youtube.com/shorts/h7_xMtNZuCo
5-Data Leakage https://www.youtube.com/shorts/FJ97DGJpa-0
4-Underfitting Problems https://www.youtube.com/shorts/5Qob73TZRAU
3-Overfitting Issues https://www.youtube.com/shorts/tjc_VvSDfxg
2-Slow Model Convergence https://www.youtube.com/shorts/-1y4S3D_JaA
1-Model Training Failure https://www.youtube.com/shorts/pMcgpmyPtp0
50-ML: Federated Learning https://www.youtube.com/shorts/A0kbmFEjAMc
49-ML: Meta-Learning https://www.youtube.com/shorts/iLKhu9dfxBY
48-ML: Word Embeddings https://www.youtube.com/shorts/0gVhua2WEbw
47-ML: Tokenization https://www.youtube.com/shorts/KHKTIaIKK5c
46-ML: Transformer Models https://www.youtube.com/shorts/WHmik9n6RWA
45-ML: Attention Mechanism https://www.youtube.com/shorts/otBZXdDQtjE
44-ML: Self-Supervised Learning https://www.youtube.com/shorts/AWGKmxV_KBg
43-ML: Markov Decision Process https://www.youtube.com/shorts/_LP2y8XaQN4
42-ML: Reinforcement Learning Policy https://www.youtube.com/shorts/O69SB9vVK2k
41-ML: Bayesian Optimization https://www.youtube.com/shorts/qkahbfunU90
40-ML: Generative Adversarial Networks https://www.youtube.com/shorts/tlRhmd0vJe8
39-ML: Autoencoders https://www.youtube.com/shorts/Twx_7BXfZF8
38-ML: Batch Normalization https://www.youtube.com/shorts/p5T6QtkaH1k
37-ML: Learning Rate https://www.youtube.com/shorts/zP9XWDz9WyM
36-ML: Early Stopping https://www.youtube.com/shorts/p6GwwPJit_0
35-ML: Precision vs. Recall https://www.youtube.com/shorts/Y4dCIz-1hP4
34-ML: F1 Score https://www.youtube.com/shorts/7ixl4RgC22M
32-ML: Confusion Matrix https://www.youtube.com/shorts/oGTJyRWHbfI
33-ML: ROC Curve https://www.youtube.com/shorts/YBgkPquZDIU
31-ML: Model Evaluation Metrics https://www.youtube.com/shorts/1dNVjARedQM
30-ML: Regularization https://www.youtube.com/shorts/jiwgUYExmGU
29-ML: Model Explainability https://www.youtube.com/shorts/ArKbh2J6qWI
28-ML: Model Deployment https://www.youtube.com/shorts/-yMNTXpX2Vc
27-ML: Imbalanced Data Handling https://www.youtube.com/shorts/kx2I6Q1FKeo
26-ML: One-Hot Encoding https://www.youtube.com/shorts/uVo31dOcNFk
25-ML: Principal Component Analysis https://www.youtube.com/shorts/iUXpYBWN3KI
24-ML: Dimensionality Reduction https://www.youtube.com/shorts/SpjFz9UPfo8
23-ML: Boosting https://www.youtube.com/shorts/aQ0wRYHJUOk
22-ML: Bagging https://www.youtube.com/shorts/JK2D9T7G_Do
21-ML: Ensemble Learning https://www.youtube.com/shorts/oJl-FDGqvTs
20-ML: Transfer Learning https://www.youtube.com/shorts/v7N3kOvx37k
19-ML: Data Augmentation https://www.youtube.com/shorts/Nqlf7DFGkDE
18 ML: Dropout Regularization https://www.youtube.com/shorts/L-PTUeta0_Y
17-ML: Backpropagation https://www.youtube.com/shorts/HkI92_Ve2ts
16-ML: Activation Functions https://www.youtube.com/shorts/AuH9FFSgAR0
- Learn Daily ML: Neural Networks https://www.youtube.com/shorts/Ly5DBvhPEX4
- Learn ML Daily: Gradient Descedent https://www.youtube.com/shorts/FhRuE6gO7lA
- Learn ML Daily: Loss Function https://www.youtube.com/shorts/b8ZHKT6JQog
- Learn ML Daily: Optimize Algorithm https://www.youtube.com/shorts/U-O_AUqGodQ
- Learn Daily ML: Hyper Parameter Tuning https://www.youtube.com/shorts/4yM1AF3AioE
- Learn Daily: ML Feature Engineering https://www.youtube.com/shorts/P2w–lhYsVU
- Learn Daily: ML Reinforcement Learning https://www.youtube.com/shorts/VPYhlHNoPiE
- Learn Daily: ML Semi-supervised Learning https://www.youtube.com/shorts/snTQdZ_diSU
- Learn Daily: ML Unsupervised Learning https://www.youtube.com/shorts/fwlbzHmvJMQ
- Learn Daily: ML Supervised Learning. https://www.youtube.com/shorts/Yg4HijY0f_o


