Data Structures, Algorithms, and Machine Learning Optimization--- Coursesghar
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- 8.6 Gradient Descent from Scratch with PyTorch-1_b9c5to06.mp4 942.9 MB
- 4.4 Quick Sort-1_alqbo35e.mp4 841.0 MB
- 4.3 Merge Sort-1_bvp4hwmr.mp4 837.9 MB
- 4.1 Binary Search-1_sgp6ncjp.mp4 661.7 MB
- 8.8 Stochastic Gradient Descent-1_4ugi2e0l.mp4 596.1 MB
- 6.2 Decision Trees-1_a1kf47jd.mp4 581.7 MB
- 2.6 Best versus Worst Case-1_3s3zu6v7.mp4 574.0 MB
- 8.1 Statistics versus Machine Learning-1_ryhdp03c.mp4 558.0 MB
- 8.9 Learning Rate Scheduling-1_rbn74jj8.mp4 480.8 MB
- 4.2 Bubble Sort-1_0rciok4o.mp4 399.8 MB
- 8.2 Objective Functions-1_mfqn5miw.mp4 389.7 MB
- 8.4 Mean Squared Error-1_2ijm8zs5.mp4 384.5 MB
- 6.4 XGBoost - Gradient-Boosted Trees-1_nqqqkuut.mp4 360.5 MB
- 2.2 Constant Time-1_mvmme7tc.mp4 328.2 MB
- 2.1 Introduction-1_3m8jqstj.mp4 321.8 MB
- 6.3 Random Forests-1_tdzchlbt.mp4 316.7 MB
- 7.3 DAGs - Directed Acyclic Graphs-1_6e7vwpti.mp4 309.5 MB
- 5.3 Hash Functions-1_69rzqd81.mp4 303.6 MB
- 1.2 A Brief History of Data-1_2b15gjsa.mp4 289.2 MB
- 2.3 Linear Time-1_lbtul2fd.mp4 272.0 MB
- 3.2 Arrays-1_ng1ex7u7.mp4 268.7 MB
- 9.4 Adaptive Optimizers-1_iiaajhex.mp4 257.7 MB
- 8.7 Critical Points-1_dqtjm5pa.mp4 230.9 MB
- 9.5 Congratulations and Next Steps-1_2f5dvgbj.mp4 224.4 MB
- 9.1 Jacobian Matrices-1_locjc786.mp4 218.9 MB
- Data Structures, Algorithms, and Machine Learning Optimization - Introduction-1_obd37x4i.mp4 209.4 MB
- 3.7 Deques-1_qiae1dix.mp4 206.0 MB
- 2.4 Polynomial Time-1_azvfdac9.mp4 197.9 MB
- 5.4 Collisions-1_hueopo2v.mp4 195.4 MB
- 5.1 Maps and Dictionaries-1_jlghq9fx.mp4 184.8 MB
- 5.7 String Keys-1_9yrxbkmz.mp4 177.1 MB
- 8.5 Minimizing Cost with Gradient Descent-1_6csagyw7.mp4 161.0 MB
- 8.3 Mean Absolute Error-1_o25rl6gv.mp4 151.6 MB
- 6.1 Introduction-1_vige31cl.mp4 148.5 MB
- 2.5 Common Runtimes-1_oc6ntre1.mp4 146.5 MB
- 5.8 Hashing in ML-1_hd4ofvqr.mp4 129.9 MB
- 3.5 Stacks-1_km4ks6ba.mp4 124.7 MB
- 5.2 Sets-1_1fu7r32o.mp4 114.8 MB
- 9.3 Momentum-1_2t8nos0w.mp4 113.8 MB
- 9.2 Second-Order Optimization and Hessians-1_p3snmxzz.mp4 112.0 MB
- 5.6 Hash Maps-1_xgfoxj80.mp4 108.4 MB
- 1.3 A Brief History of Algorithms-1_t7p43t0a.mp4 108.3 MB
- 5.5 Load Factor-1_1o6rzf14.mp4 98.8 MB
- 3.3 Linked Lists-1_9mdvvbl1.mp4 96.9 MB
- 8.10 Maximizing Reward with Gradient Ascent-1_sjmahkxl.mp4 87.1 MB
- 1.1 Orientation to the Machine Learning Foundations Series-1_j225u2zw.mp4 85.2 MB
- 1.4 Applications to Machine Learning-1_0mwik9nq.mp4 81.3 MB
- 3.1 Lists-1_xq8t62k3.mp4 76.6 MB
- 6.5 Additional Concepts-1_pe96vxli.mp4 72.8 MB
- 7.1 Introduction-1_zrs05h1z.mp4 71.8 MB
- 3.6 Queues-1_fb1syknh.mp4 66.3 MB
- Data Structures, Algorithms, and Machine Learning Optimization - Summary-1_c7y8c31a.mp4 60.6 MB
- 7.5 Bonus - Pandas DataFrames-1_0qdxrtbz.mp4 57.2 MB
- 7.6 Resources for Further Study of DSA-1_yotxi7qk.mp4 53.9 MB
- Topics-1_ojmlg5t3.mp4 47.8 MB
- 7.4 Additional Concepts-1_gs4yyv04.mp4 47.0 MB
- 3.4 Doubly-Linked Lists-1_mg3e611v.mp4 44.8 MB
- 7.2 Directed versus Undirected Graphs-1_8owxblcg.mp4 41.9 MB
- Topics-1_lnxw7w1d.mp4 39.8 MB
- Topics-1_14lwnrox.mp4 38.4 MB
- Topics-1_h8oxrxkq.mp4 33.1 MB
- Topics-1_9l2kqjwl.mp4 30.3 MB
- Topics-1_6t08jff9.mp4 28.3 MB
- Topics-1_k8xqbx14.mp4 25.4 MB
- Topics-1_il0kt54q.mp4 22.9 MB
- Topics-1_z0h0ef88.mp4 19.3 MB
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